Modifying a dispersed storage network memory data access response plan

ABSTRACT

A dispersed storage network memory includes a pool of storage nodes, where the pool of storage nodes stores a multitude of encoded data files. A storage node obtains and analyzes data access response performance data for each of the storage nodes to produce a modified data access response plan that includes identity of an undesired performing storage node and an alternative data access response for the undesired performing storage node. The storage nodes receive corresponding portions of a data access request for at least a portion of one of the multitude of encoded data files. The undesired performing storage node or another storage node processes one of the corresponding portions of the data access request in accordance with the alternative data access response.

CROSS REFERENCE TO RELATED PATENTS

The present U.S. Utility patent application claims priority pursuant to35 U.S.C. §119(e) to the following U.S. Provisional patent applicationwhich is hereby incorporated herein by reference in its entirety andmade part of the present U.S. Utility patent application for allpurposes:

1. U.S. Provisional Application Ser. No. 61/761,005, entitled “ACCESSINGDATA IN A DISPERSED STORAGE NETWORK,” (Attorney Docket No. CS01289),filed Feb. 5, 2013, pending.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

NOT APPLICABLE

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

NOT APPLICABLE

BACKGROUND OF THE INVENTION

1. Technical Field of the Invention

This invention relates generally to computer networks and moreparticularly to dispersed storage of data and distributed taskprocessing of data.

2. Description of Related Art

Computing devices are known to communicate data, process data, and/orstore data. Such computing devices range from wireless smart phones,laptops, tablets, personal computers (PC), work stations, video gamedevices, to data centers that support millions of web searches, stocktrades, or on-line purchases every day. In general, a computing deviceincludes a central processing unit (CPU), a memory system, userinput/output interfaces, peripheral device interfaces, and aninterconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using“cloud computing” to perform one or more computing functions (e.g., aservice, an application, an algorithm, an arithmetic logic function,etc.) on behalf of the computer. Further, for large services,applications, and/or functions, cloud computing may be performed bymultiple cloud computing resources in a distributed manner to improvethe response time for completion of the service, application, and/orfunction. For example, Hadoop is an open source software framework thatsupports distributed applications enabling application execution bythousands of computers.

In addition to cloud computing, a computer may use “cloud storage” aspart of its memory system. As is known, cloud storage enables a user,via its computer, to store files, applications, etc., on an Internetstorage system. The Internet storage system may include a RAID(redundant array of independent disks) system and/or a dispersed storagesystem that uses an error correction scheme to encode data for storage.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a distributedcomputing system in accordance with the present invention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present invention;

FIG. 3 is a diagram of an example of a distributed storage and taskprocessing in accordance with the present invention;

FIG. 4 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing in accordance with thepresent invention;

FIG. 5 is a logic diagram of an example of a method for outbound DSTprocessing in accordance with the present invention;

FIG. 6 is a schematic block diagram of an embodiment of a dispersederror encoding in accordance with the present invention;

FIG. 7 is a diagram of an example of a segment processing of thedispersed error encoding in accordance with the present invention;

FIG. 8 is a diagram of an example of error encoding and slicingprocessing of the dispersed error encoding in accordance with thepresent invention;

FIG. 9 is a diagram of an example of grouping selection processing ofthe outbound DST processing in accordance with the present invention;

FIG. 10 is a diagram of an example of converting data into slice groupsin accordance with the present invention;

FIG. 11 is a schematic block diagram of an embodiment of a DST executionunit in accordance with the present invention;

FIG. 12 is a schematic block diagram of an example of operation of a DSTexecution unit in accordance with the present invention;

FIG. 13 is a schematic block diagram of an embodiment of an inbounddistributed storage and/or task (DST) processing in accordance with thepresent invention;

FIG. 14 is a logic diagram of an example of a method for inbound DSTprocessing in accordance with the present invention;

FIG. 15 is a diagram of an example of de-grouping selection processingof the inbound DST processing in accordance with the present invention;

FIG. 16 is a schematic block diagram of an embodiment of a dispersederror decoding in accordance with the present invention;

FIG. 17 is a diagram of an example of de-slicing and error decodingprocessing of the dispersed error decoding in accordance with thepresent invention;

FIG. 18 is a diagram of an example of a de-segment processing of thedispersed error decoding in accordance with the present invention;

FIG. 19 is a diagram of an example of converting slice groups into datain accordance with the present invention;

FIG. 20 is a diagram of an example of a distributed storage within thedistributed computing system in accordance with the present invention;

FIG. 21 is a schematic block diagram of an example of operation ofoutbound distributed storage and/or task (DST) processing for storingdata in accordance with the present invention;

FIG. 22 is a schematic block diagram of an example of a dispersed errorencoding for the example of FIG. 21 in accordance with the presentinvention;

FIG. 23 is a diagram of an example of converting data into pillar slicegroups for storage in accordance with the present invention;

FIG. 24 is a schematic block diagram of an example of a storageoperation of a DST execution unit in accordance with the presentinvention;

FIG. 25 is a schematic block diagram of an example of operation ofinbound distributed storage and/or task (DST) processing for retrievingdispersed error encoded data in accordance with the present invention;

FIG. 26 is a schematic block diagram of an example of a dispersed errordecoding for the example of FIG. 25 in accordance with the presentinvention;

FIG. 27 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing a plurality ofdata and a plurality of task codes in accordance with the presentinvention;

FIG. 28 is a schematic block diagram of an example of the distributedcomputing system performing tasks on stored data in accordance with thepresent invention;

FIG. 29 is a schematic block diagram of an embodiment of a taskdistribution module facilitating the example of FIG. 28 in accordancewith the present invention;

FIG. 30 is a diagram of a specific example of the distributed computingsystem performing tasks on stored data in accordance with the presentinvention;

FIG. 31 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing data and taskcodes for the example of FIG. 30 in accordance with the presentinvention;

FIG. 32 is a diagram of an example of DST allocation information for theexample of FIG. 30 in accordance with the present invention;

FIGS. 33-38 are schematic block diagrams of the DSTN module performingthe example of FIG. 30 in accordance with the present invention;

FIG. 39 is a diagram of an example of combining result information intofinal results for the example of FIG. 30 in accordance with the presentinvention;

FIG. 40A is a schematic block diagram of another embodiment of adistributed computing system in accordance with the present invention;

FIG. 40B is a flowchart illustrating an example of executing distributedcomputing tasks in accordance with the present invention;

FIG. 41A is a schematic block diagram of another embodiment of adistributed computing system in accordance with the present invention;

FIG. 41B is a flowchart illustrating an example of executing tasks inaccordance with the present invention;

FIG. 42A is a schematic block diagram of another embodiment of adistributed computing system in accordance with the present invention;

FIG. 42B is a flowchart illustrating an example of validating access inaccordance with the present invention;

FIG. 43A is a schematic block diagram of another embodiment of adistributed computing system in accordance with the present invention;

FIG. 43B is a flowchart illustrating an example of accessing data inaccordance with the present invention;

FIGS. 44A, B, D, E, F are schematic block diagrams of an embodiment of adispersed storage network (DSN) illustrating example steps of modifyinga DSN memory data access response plan in accordance with the presentinvention;

FIG. 44C is a diagram illustrating an example of a storage node poolassignment table in accordance with the present invention;

FIG. 44G is a flowchart illustrating an example of modifying a dispersedstorage network (DSN) memory data access response plan in accordancewith the present invention;

FIG. 45A is a schematic block diagram of another embodiment of adispersed storage system in accordance with the present invention; and

FIG. 45B is a flowchart illustrating an example of storing data inaccordance with the present invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a distributedcomputing system 10 that includes a user device 12 and/or a user device14, a distributed storage and/or task (DST) processing unit 16, adistributed storage and/or task network (DSTN) managing unit 18, a DSTintegrity processing unit 20, and a distributed storage and/or tasknetwork (DSTN) module 22. The components of the distributed computingsystem 10 are coupled via a network 24, which may include one or morewireless and/or wire lined communication systems; one or more privateintranet systems and/or public internet systems; and/or one or morelocal area networks (LAN) and/or wide area networks (WAN).

The DSTN module 22 includes a plurality of distributed storage and/ortask (DST) execution units 36 that may be located at geographicallydifferent sites (e.g., one in Chicago, one in Milwaukee, etc.). Each ofthe DST execution units is operable to store dispersed error encodeddata and/or to execute, in a distributed manner, one or more tasks ondata. The tasks may be a simple function (e.g., a mathematical function,a logic function, an identify function, a find function, a search enginefunction, a replace function, etc.), a complex function (e.g.,compression, human and/or computer language translation, text-to-voiceconversion, voice-to-text conversion, etc.), multiple simple and/orcomplex functions, one or more algorithms, one or more applications,etc.

Each of the user devices 12-14, the DST processing unit 16, the DSTNmanaging unit 18, and the DST integrity processing unit 20 include acomputing core 26 and may be a portable computing device and/or a fixedcomputing device. A portable computing device may be a social networkingdevice, a gaming device, a cell phone, a smart phone, a personal digitalassistant, a digital music player, a digital video player, a laptopcomputer, a handheld computer, a tablet, a video game controller, and/orany other portable device that includes a computing core. A fixedcomputing device may be a personal computer (PC), a computer server, acable set-top box, a satellite receiver, a television set, a printer, afax machine, home entertainment equipment, a video game console, and/orany type of home or office computing equipment. User device 12 and DSTprocessing unit 16 are configured to include a DST client module 34.

With respect to interfaces, each interface 30, 32, and 33 includessoftware and/or hardware to support one or more communication links viathe network 24 indirectly and/or directly. For example, interfaces 30support a communication link (e.g., wired, wireless, direct, via a LAN,via the network 24, etc.) between user device 14 and the DST processingunit 16. As another example, interface 32 supports communication links(e.g., a wired connection, a wireless connection, a LAN connection,and/or any other type of connection to/from the network 24) between userdevice 12 and the DSTN module 22 and between the DST processing unit 16and the DSTN module 22. As yet another example, interface 33 supports acommunication link for each of the DSTN managing unit 18 and DSTintegrity processing unit 20 to the network 24.

The distributed computing system 10 is operable to support dispersedstorage (DS) error encoded data storage and retrieval, to supportdistributed task processing on received data, and/or to supportdistributed task processing on stored data. In general and with respectto DS error encoded data storage and retrieval, the distributedcomputing system 10 supports three primary operations: storagemanagement, data storage and retrieval (an example of which will bediscussed with reference to FIGS. 20-26), and data storage integrityverification. In accordance with these three primary functions, data canbe encoded, distributedly stored in physically different locations, andsubsequently retrieved in a reliable and secure manner. Such a system istolerant of a significant number of failures (e.g., up to a failurelevel, which may be greater than or equal to a pillar width minus adecode threshold minus one) that may result from individual storagedevice failures and/or network equipment failures without loss of dataand without the need for a redundant or backup copy. Further, the systemallows the data to be stored for an indefinite period of time withoutdata loss and does so in a secure manner (e.g., the system is veryresistant to attempts at hacking the data).

The second primary function (i.e., distributed data storage andretrieval) begins and ends with a user device 12-14. For instance, if asecond type of user device 14 has data 40 to store in the DSTN module22, it sends the data 40 to the DST processing unit 16 via its interface30. The interface 30 functions to mimic a conventional operating system(OS) file system interface (e.g., network file system (NFS), flash filesystem (FFS), disk file system (DFS), file transfer protocol (FTP),web-based distributed authoring and versioning (WebDAV), etc.) and/or ablock memory interface (e.g., small computer system interface (SCSI),internet small computer system interface (iSCSI), etc.). In addition,the interface 30 may attach a user identification code (ID) to the data40.

To support storage management, the DSTN managing unit 18 performs DSmanagement services. One such DS management service includes the DSTNmanaging unit 18 establishing distributed data storage parameters (e.g.,vault creation, distributed storage parameters, security parameters,billing information, user profile information, etc.) for a user device12-14 individually or as part of a group of user devices. For example,the DSTN managing unit 18 coordinates creation of a vault (e.g., avirtual memory block) within memory of the DSTN module 22 for a userdevice, a group of devices, or for public access and establishes pervault dispersed storage (DS) error encoding parameters for a vault. TheDSTN managing unit 18 may facilitate storage of DS error encodingparameters for each vault of a plurality of vaults by updating registryinformation for the distributed computing system 10. The facilitatingincludes storing updated registry information in one or more of the DSTNmodule 22, the user device 12, the DST processing unit 16, and the DSTintegrity processing unit 20.

The DS error encoding parameters (e.g., or dispersed storage errorcoding parameters) include data segmenting information (e.g., how manysegments data (e.g., a file, a group of files, a data block, etc.) isdivided into), segment security information (e.g., per segmentencryption, compression, integrity checksum, etc.), error codinginformation (e.g., pillar width, decode threshold, read threshold, writethreshold, etc.), slicing information (e.g., the number of encoded dataslices that will be created for each data segment); and slice securityinformation (e.g., per encoded data slice encryption, compression,integrity checksum, etc.).

The DSTN managing module 18 creates and stores user profile information(e.g., an access control list (ACL)) in local memory and/or withinmemory of the DSTN module 22. The user profile information includesauthentication information, permissions, and/or the security parameters.The security parameters may include encryption/decryption scheme, one ormore encryption keys, key generation scheme, and/or dataencoding/decoding scheme.

The DSTN managing unit 18 creates billing information for a particularuser, a user group, a vault access, public vault access, etc. Forinstance, the DSTN managing unit 18 tracks the number of times a useraccesses a private vault and/or public vaults, which can be used togenerate a per-access billing information. In another instance, the DSTNmanaging unit 18 tracks the amount of data stored and/or retrieved by auser device and/or a user group, which can be used to generate aper-data-amount billing information.

Another DS management service includes the DSTN managing unit 18performing network operations, network administration, and/or networkmaintenance. Network operations includes authenticating user dataallocation requests (e.g., read and/or write requests), managingcreation of vaults, establishing authentication credentials for userdevices, adding/deleting components (e.g., user devices, DST executionunits, and/or DST processing units) from the distributed computingsystem 10, and/or establishing authentication credentials for DSTexecution units 36. Network administration includes monitoring devicesand/or units for failures, maintaining vault information, determiningdevice and/or unit activation status, determining device and/or unitloading, and/or determining any other system level operation thataffects the performance level of the system 10. Network maintenanceincludes facilitating replacing, upgrading, repairing, and/or expandinga device and/or unit of the system 10.

To support data storage integrity verification within the distributedcomputing system 10, the DST integrity processing unit 20 performsrebuilding of ‘bad’ or missing encoded data slices. At a high level, theDST integrity processing unit 20 performs rebuilding by periodicallyattempting to retrieve/list encoded data slices, and/or slice names ofthe encoded data slices, from the DSTN module 22. For retrieved encodedslices, they are checked for errors due to data corruption, outdatedversion, etc. If a slice includes an error, it is flagged as a ‘bad’slice. For encoded data slices that were not received and/or not listed,they are flagged as missing slices. Bad and/or missing slices aresubsequently rebuilt using other retrieved encoded data slices that aredeemed to be good slices to produce rebuilt slices. The rebuilt slicesare stored in memory of the DSTN module 22. Note that the DST integrityprocessing unit 20 may be a separate unit as shown, it may be includedin the DSTN module 22, it may be included in the DST processing unit 16,and/or distributed among the DST execution units 36.

To support distributed task processing on received data, the distributedcomputing system 10 has two primary operations: DST (distributed storageand/or task processing) management and DST execution on received data(an example of which will be discussed with reference to FIGS. 3-19).With respect to the storage portion of the DST management, the DSTNmanaging unit 18 functions as previously described. With respect to thetasking processing of the DST management, the DSTN managing unit 18performs distributed task processing (DTP) management services. One suchDTP management service includes the DSTN managing unit 18 establishingDTP parameters (e.g., user-vault affiliation information, billinginformation, user-task information, etc.) for a user device 12-14individually or as part of a group of user devices.

Another DTP management service includes the DSTN managing unit 18performing DTP network operations, network administration (which isessentially the same as described above), and/or network maintenance(which is essentially the same as described above). Network operationsincludes, but is not limited to, authenticating user task processingrequests (e.g., valid request, valid user, etc.), authenticating resultsand/or partial results, establishing DTP authentication credentials foruser devices, adding/deleting components (e.g., user devices, DSTexecution units, and/or DST processing units) from the distributedcomputing system, and/or establishing DTP authentication credentials forDST execution units.

To support distributed task processing on stored data, the distributedcomputing system 10 has two primary operations: DST (distributed storageand/or task) management and DST execution on stored data. With respectto the DST execution on stored data, if the second type of user device14 has a task request 38 for execution by the DSTN module 22, it sendsthe task request 38 to the DST processing unit 16 via its interface 30.An example of DST execution on stored data will be discussed in greaterdetail with reference to FIGS. 27-39. With respect to the DSTmanagement, it is substantially similar to the DST management to supportdistributed task processing on received data.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (TO)controller 56, a peripheral component interconnect (PCI) interface 58,an IO interface module 60, at least one IO device interface module 62, aread only memory (ROM) basic input output system (BIOS) 64, and one ormore memory interface modules. The one or more memory interfacemodule(s) includes one or more of a universal serial bus (USB) interfacemodule 66, a host bus adapter (HBA) interface module 68, a networkinterface module 70, a flash interface module 72, a hard drive interfacemodule 74, and a DSTN interface module 76.

The DSTN interface module 76 functions to mimic a conventional operatingsystem (OS) file system interface (e.g., network file system (NFS),flash file system (FFS), disk file system (DFS), file transfer protocol(FTP), web-based distributed authoring and versioning (WebDAV), etc.)and/or a block memory interface (e.g., small computer system interface(SCSI), internet small computer system interface (iSCSI), etc.). TheDSTN interface module 76 and/or the network interface module 70 mayfunction as the interface 30 of the user device 14 of FIG. 1. Furthernote that the IO device interface module 62 and/or the memory interfacemodules may be collectively or individually referred to as IO ports.

FIG. 3 is a diagram of an example of the distributed computing systemperforming a distributed storage and task processing operation. Thedistributed computing system includes a DST (distributed storage and/ortask) client module 34 (which may be in user device 14 and/or in DSTprocessing unit 16 of FIG. 1), a network 24, a plurality of DSTexecution units 1-n that includes two or more DST execution units 36 ofFIG. 1 (which form at least a portion of DSTN module 22 of FIG. 1), aDST managing module (not shown), and a DST integrity verification module(not shown). The DST client module 34 includes an outbound DSTprocessing section 80 and an inbound DST processing section 82. Each ofthe DST execution units 1-n includes a controller 86, a processingmodule 84, memory 88, a DT (distributed task) execution module 90, and aDST client module 34.

In an example of operation, the DST client module 34 receives data 92and one or more tasks 94 to be performed upon the data 92. The data 92may be of any size and of any content, where, due to the size (e.g.,greater than a few Terra-Bytes), the content (e.g., secure data, etc.),and/or task(s) (e.g., MIPS intensive), distributed processing of thetask(s) on the data is desired. For example, the data 92 may be one ormore digital books, a copy of a company's emails, a large-scale Internetsearch, a video security file, one or more entertainment video files(e.g., television programs, movies, etc.), data files, and/or any otherlarge amount of data (e.g., greater than a few Terra-Bytes).

Within the DST client module 34, the outbound DST processing section 80receives the data 92 and the task(s) 94. The outbound DST processingsection 80 processes the data 92 to produce slice groupings 96. As anexample of such processing, the outbound DST processing section 80partitions the data 92 into a plurality of data partitions. For eachdata partition, the outbound DST processing section 80 dispersed storage(DS) error encodes the data partition to produce encoded data slices andgroups the encoded data slices into a slice grouping 96. In addition,the outbound DST processing section 80 partitions the task 94 intopartial tasks 98, where the number of partial tasks 98 may correspond tothe number of slice groupings 96.

The outbound DST processing section 80 then sends, via the network 24,the slice groupings 96 and the partial tasks 98 to the DST executionunits 1-n of the DSTN module 22 of FIG. 1. For example, the outbound DSTprocessing section 80 sends slice group 1 and partial task 1 to DSTexecution unit 1. As another example, the outbound DST processingsection 80 sends slice group #n and partial task #n to DST executionunit #n.

Each DST execution unit performs its partial task 98 upon its slicegroup 96 to produce partial results 102. For example, DST execution unit#1 performs partial task #1 on slice group #1 to produce a partialresult #1, for results. As a more specific example, slice group #1corresponds to a data partition of a series of digital books and thepartial task #1 corresponds to searching for specific phrases, recordingwhere the phrase is found, and establishing a phrase count. In this morespecific example, the partial result #1 includes information as to wherethe phrase was found and includes the phrase count.

Upon completion of generating their respective partial results 102, theDST execution units send, via the network 24, their partial results 102to the inbound DST processing section 82 of the DST client module 34.The inbound DST processing section 82 processes the received partialresults 102 to produce a result 104. Continuing with the specificexample of the preceding paragraph, the inbound DST processing section82 combines the phrase count from each of the DST execution units 36 toproduce a total phrase count. In addition, the inbound DST processingsection 82 combines the ‘where the phrase was found’ information fromeach of the DST execution units 36 within their respective datapartitions to produce ‘where the phrase was found’ information for theseries of digital books.

In another example of operation, the DST client module 34 requestsretrieval of stored data within the memory of the DST execution units 36(e.g., memory of the DSTN module). In this example, the task 94 isretrieve data stored in the memory of the DSTN module. Accordingly, theoutbound DST processing section 80 converts the task 94 into a pluralityof partial tasks 98 and sends the partial tasks 98 to the respective DSTexecution units 1-n.

In response to the partial task 98 of retrieving stored data, a DSTexecution unit 36 identifies the corresponding encoded data slices 100and retrieves them. For example, DST execution unit #1 receives partialtask #1 and retrieves, in response thereto, retrieved slices #1. The DSTexecution units 36 send their respective retrieved slices 100 to theinbound DST processing section 82 via the network 24.

The inbound DST processing section 82 converts the retrieved slices 100into data 92. For example, the inbound DST processing section 82de-groups the retrieved slices 100 to produce encoded slices per datapartition. The inbound DST processing section 82 then DS error decodesthe encoded slices per data partition to produce data partitions. Theinbound DST processing section 82 de-partitions the data partitions torecapture the data 92.

FIG. 4 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing section 80 of a DSTclient module 34 FIG. 1 coupled to a DSTN module 22 of a FIG. 1 (e.g., aplurality of n DST execution units 36) via a network 24. The outboundDST processing section 80 includes a data partitioning module 110, adispersed storage (DS) error encoding module 112, a grouping selectormodule 114, a control module 116, and a distributed task control module118.

In an example of operation, the data partitioning module 110 partitionsdata 92 into a plurality of data partitions 120. The number ofpartitions and the size of the partitions may be selected by the controlmodule 116 via control 160 based on the data 92 (e.g., its size, itscontent, etc.), a corresponding task 94 to be performed (e.g., simple,complex, single step, multiple steps, etc.), DS encoding parameters(e.g., pillar width, decode threshold, write threshold, segment securityparameters, slice security parameters, etc.), capabilities of the DSTexecution units 36 (e.g., processing resources, availability ofprocessing recourses, etc.), and/or as may be inputted by a user, systemadministrator, or other operator (human or automated). For example, thedata partitioning module 110 partitions the data 92 (e.g., 100Terra-Bytes) into 100,000 data segments, each being 1 Giga-Byte in size.Alternatively, the data partitioning module 110 partitions the data 92into a plurality of data segments, where some of data segments are of adifferent size, are of the same size, or a combination thereof.

The DS error encoding module 112 receives the data partitions 120 in aserial manner, a parallel manner, and/or a combination thereof. For eachdata partition 120, the DS error encoding module 112 DS error encodesthe data partition 120 in accordance with control information 160 fromthe control module 116 to produce encoded data slices 122. The DS errorencoding includes segmenting the data partition into data segments,segment security processing (e.g., encryption, compression,watermarking, integrity check (e.g., CRC), etc.), error encoding,slicing, and/or per slice security processing (e.g., encryption,compression, watermarking, integrity check (e.g., CRC), etc.). Thecontrol information 160 indicates which steps of the DS error encodingare active for a given data partition and, for active steps, indicatesthe parameters for the step. For example, the control information 160indicates that the error encoding is active and includes error encodingparameters (e.g., pillar width, decode threshold, write threshold, readthreshold, type of error encoding, etc.).

The group selecting module 114 groups the encoded slices 122 of a datapartition into a set of slice groupings 96. The number of slicegroupings corresponds to the number of DST execution units 36 identifiedfor a particular task 94. For example, if five DST execution units 36are identified for the particular task 94, the group selecting modulegroups the encoded slices 122 of a data partition into five slicegroupings 96. The group selecting module 114 outputs the slice groupings96 to the corresponding DST execution units 36 via the network 24.

The distributed task control module 118 receives the task 94 andconverts the task 94 into a set of partial tasks 98. For example, thedistributed task control module 118 receives a task to find where in thedata (e.g., a series of books) a phrase occurs and a total count of thephrase usage in the data. In this example, the distributed task controlmodule 118 replicates the task 94 for each DST execution unit 36 toproduce the partial tasks 98. In another example, the distributed taskcontrol module 118 receives a task to find where in the data a firstphrase occurs, wherein in the data a second phrase occurs, and a totalcount for each phrase usage in the data. In this example, thedistributed task control module 118 generates a first set of partialtasks 98 for finding and counting the first phase and a second set ofpartial tasks for finding and counting the second phrase. Thedistributed task control module 118 sends respective first and/or secondpartial tasks 98 to each DST execution unit 36.

FIG. 5 is a logic diagram of an example of a method for outbounddistributed storage and task (DST) processing that begins at step 126where a DST client module receives data and one or more correspondingtasks. The method continues at step 128 where the DST client moduledetermines a number of DST units to support the task for one or moredata partitions. For example, the DST client module may determine thenumber of DST units to support the task based on the size of the data,the requested task, the content of the data, a predetermined number(e.g., user indicated, system administrator determined, etc.), availableDST units, capability of the DST units, and/or any other factorregarding distributed task processing of the data. The DST client modulemay select the same DST units for each data partition, may selectdifferent DST units for the data partitions, or a combination thereof.

The method continues at step 130 where the DST client module determinesprocessing parameters of the data based on the number of DST unitsselected for distributed task processing. The processing parametersinclude data partitioning information, DS encoding parameters, and/orslice grouping information. The data partitioning information includes anumber of data partitions, size of each data partition, and/ororganization of the data partitions (e.g., number of data blocks in apartition, the size of the data blocks, and arrangement of the datablocks). The DS encoding parameters include segmenting information,segment security information, error encoding information (e.g.,dispersed storage error encoding function parameters including one ormore of pillar width, decode threshold, write threshold, read threshold,generator matrix), slicing information, and/or per slice securityinformation. The slice grouping information includes informationregarding how to arrange the encoded data slices into groups for theselected DST units. As a specific example, if the DST client moduledetermines that five DST units are needed to support the task, then itdetermines that the error encoding parameters include a pillar width offive and a decode threshold of three.

The method continues at step 132 where the DST client module determinestask partitioning information (e.g., how to partition the tasks) basedon the selected DST units and data processing parameters. The dataprocessing parameters include the processing parameters and DST unitcapability information. The DST unit capability information includes thenumber of DT (distributed task) execution units, execution capabilitiesof each DT execution unit (e.g., MIPS capabilities, processing resources(e.g., quantity and capability of microprocessors, CPUs, digital signalprocessors, co-processor, microcontrollers, arithmetic logic circuitry,and/or and the other analog and/or digital processing circuitry),availability of the processing resources, memory information (e.g.,type, size, availability, etc.)), and/or any information germane toexecuting one or more tasks.

The method continues at step 134 where the DST client module processesthe data in accordance with the processing parameters to produce slicegroupings. The method continues at step 136 where the DST client modulepartitions the task based on the task partitioning information toproduce a set of partial tasks. The method continues at step 138 wherethe DST client module sends the slice groupings and the correspondingpartial tasks to respective DST units.

FIG. 6 is a schematic block diagram of an embodiment of the dispersedstorage (DS) error encoding module 112 of an outbound distributedstorage and task (DST) processing section. The DS error encoding module112 includes a segment processing module 142, a segment securityprocessing module 144, an error encoding module 146, a slicing module148, and a per slice security processing module 150. Each of thesemodules is coupled to a control module 116 to receive controlinformation 160 therefrom.

In an example of operation, the segment processing module 142 receives adata partition 120 from a data partitioning module and receivessegmenting information as the control information 160 from the controlmodule 116. The segmenting information indicates how the segmentprocessing module 142 is to segment the data partition 120. For example,the segmenting information indicates how many rows to segment the databased on a decode threshold of an error encoding scheme, indicates howmany columns to segment the data into based on a number and size of datablocks within the data partition 120, and indicates how many columns toinclude in a data segment 152. The segment processing module 142segments the data 120 into data segments 152 in accordance with thesegmenting information.

The segment security processing module 144, when enabled by the controlmodule 116, secures the data segments 152 based on segment securityinformation received as control information 160 from the control module116. The segment security information includes data compression,encryption, watermarking, integrity check (e.g., cyclic redundancy check(CRC), etc.), and/or any other type of digital security. For example,when the segment security processing module 144 is enabled, it maycompress a data segment 152, encrypt the compressed data segment, andgenerate a CRC value for the encrypted data segment to produce a securedata segment 154. When the segment security processing module 144 is notenabled, it passes the data segments 152 to the error encoding module146 or is bypassed such that the data segments 152 are provided to theerror encoding module 146.

The error encoding module 146 encodes the secure data segments 154 inaccordance with error correction encoding parameters received as controlinformation 160 from the control module 116. The error correctionencoding parameters (e.g., also referred to as dispersed storage errorcoding parameters) include identifying an error correction encodingscheme (e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an online coding algorithm, an information dispersalalgorithm, etc.), a pillar width, a decode threshold, a read threshold,a write threshold, etc. For example, the error correction encodingparameters identify a specific error correction encoding scheme,specifies a pillar width of five, and specifies a decode threshold ofthree. From these parameters, the error encoding module 146 encodes adata segment 154 to produce an encoded data segment 156.

The slicing module 148 slices the encoded data segment 156 in accordancewith the pillar width of the error correction encoding parametersreceived as control information 160. For example, if the pillar width isfive, the slicing module 148 slices an encoded data segment 156 into aset of five encoded data slices. As such, for a plurality of encodeddata segments 156 for a given data partition, the slicing module outputsa plurality of sets of encoded data slices 158.

The per slice security processing module 150, when enabled by thecontrol module 116, secures each encoded data slice 158 based on slicesecurity information received as control information 160 from thecontrol module 116. The slice security information includes datacompression, encryption, watermarking, integrity check (e.g., CRC,etc.), and/or any other type of digital security. For example, when theper slice security processing module 150 is enabled, it compresses anencoded data slice 158, encrypts the compressed encoded data slice, andgenerates a CRC value for the encrypted encoded data slice to produce asecure encoded data slice 122. When the per slice security processingmodule 150 is not enabled, it passes the encoded data slices 158 or isbypassed such that the encoded data slices 158 are the output of the DSerror encoding module 112. Note that the control module 116 may beomitted and each module stores its own parameters.

FIG. 7 is a diagram of an example of a segment processing of a dispersedstorage (DS) error encoding module. In this example, a segmentprocessing module 142 receives a data partition 120 that includes 45data blocks (e.g., d1-d45), receives segmenting information (i.e.,control information 160) from a control module, and segments the datapartition 120 in accordance with the control information 160 to producedata segments 152. Each data block may be of the same size as other datablocks or of a different size. In addition, the size of each data blockmay be a few bytes to megabytes of data. As previously mentioned, thesegmenting information indicates how many rows to segment the datapartition into, indicates how many columns to segment the data partitioninto, and indicates how many columns to include in a data segment.

In this example, the decode threshold of the error encoding scheme isthree; as such the number of rows to divide the data partition into isthree. The number of columns for each row is set to 15, which is basedon the number and size of data blocks. The data blocks of the datapartition are arranged in rows and columns in a sequential order (i.e.,the first row includes the first 15 data blocks; the second row includesthe second 15 data blocks; and the third row includes the last 15 datablocks).

With the data blocks arranged into the desired sequential order, theyare divided into data segments based on the segmenting information. Inthis example, the data partition is divided into 8 data segments; thefirst 7 include 2 columns of three rows and the last includes 1 columnof three rows. Note that the first row of the 8 data segments is insequential order of the first 15 data blocks; the second row of the 8data segments in sequential order of the second 15 data blocks; and thethird row of the 8 data segments in sequential order of the last 15 datablocks. Note that the number of data blocks, the grouping of the datablocks into segments, and size of the data blocks may vary toaccommodate the desired distributed task processing function.

FIG. 8 is a diagram of an example of error encoding and slicingprocessing of the dispersed error encoding processing the data segmentsof FIG. 7. In this example, data segment 1 includes 3 rows with each rowbeing treated as one word for encoding. As such, data segment 1 includesthree words for encoding: word 1 including data blocks d1 and d2, word 2including data blocks d16 and d17, and word 3 including data blocks d31and d32. Each of data segments 2-7 includes three words where each wordincludes two data blocks. Data segment 8 includes three words where eachword includes a single data block (e.g., d15, d30, and d45).

In operation, an error encoding module 146 and a slicing module 148convert each data segment into a set of encoded data slices inaccordance with error correction encoding parameters as controlinformation 160. More specifically, when the error correction encodingparameters indicate a unity matrix Reed-Solomon based encodingalgorithm, 5 pillars, and decode threshold of 3, the first three encodeddata slices of the set of encoded data slices for a data segment aresubstantially similar to the corresponding word of the data segment. Forinstance, when the unity matrix Reed-Solomon based encoding algorithm isapplied to data segment 1, the content of the first encoded data slice(DS1_d1&2) of the first set of encoded data slices (e.g., correspondingto data segment 1) is substantially similar to content of the first word(e.g., d1 & d2); the content of the second encoded data slice(DS1_d16&17) of the first set of encoded data slices is substantiallysimilar to content of the second word (e.g., d16 & d17); and the contentof the third encoded data slice (DS1_d31&32) of the first set of encodeddata slices is substantially similar to content of the third word (e.g.,d31 & d32).

The content of the fourth and fifth encoded data slices (e.g., ES1_(—)1and ES1_(—)2) of the first set of encoded data slices include errorcorrection data based on the first—third words of the first datasegment. With such an encoding and slicing scheme, retrieving any threeof the five encoded data slices allows the data segment to be accuratelyreconstructed.

The encoding and slices of data segments 2-7 yield sets of encoded dataslices similar to the set of encoded data slices of data segment 1. Forinstance, the content of the first encoded data slice (DS2_d3&4) of thesecond set of encoded data slices (e.g., corresponding to data segment2) is substantially similar to content of the first word (e.g., d3 &d4); the content of the second encoded data slice (DS2_d18&19) of thesecond set of encoded data slices is substantially similar to content ofthe second word (e.g., d18 & d19); and the content of the third encodeddata slice (DS2_d33&34) of the second set of encoded data slices issubstantially similar to content of the third word (e.g., d33 & d34).The content of the fourth and fifth encoded data slices (e.g., ES1_(—)1and ES1_(—)2) of the second set of encoded data slices includes errorcorrection data based on the first—third words of the second datasegment.

FIG. 9 is a diagram of an example of grouping selection processing of anoutbound distributed storage and task (DST) processing in accordancewith group selection information as control information 160 from acontrol module. Encoded slices for data partition 122 are grouped inaccordance with the control information 160 to produce slice groupings96. In this example, a grouping selection module 114 organizes theencoded data slices into five slice groupings (e.g., one for each DSTexecution unit of a distributed storage and task network (DSTN) module).As a specific example, the grouping selection module 114 creates a firstslice grouping for a DST execution unit #1, which includes first encodedslices of each of the sets of encoded slices. As such, the first DSTexecution unit receives encoded data slices corresponding to data blocks1-15 (e.g., encoded data slices of contiguous data).

The grouping selection module 114 also creates a second slice groupingfor a DST execution unit #2, which includes second encoded slices ofeach of the sets of encoded slices. As such, the second DST executionunit receives encoded data slices corresponding to data blocks 16-30.The grouping selection module 114 further creates a third slice groupingfor DST execution unit #3, which includes third encoded slices of eachof the sets of encoded slices. As such, the third DST execution unitreceives encoded data slices corresponding to data blocks 31-45.

The grouping selection module 114 creates a fourth slice grouping forDST execution unit #4, which includes fourth encoded slices of each ofthe sets of encoded slices. As such, the fourth DST execution unitreceives encoded data slices corresponding to first error encodinginformation (e.g., encoded data slices of error coding (EC) data). Thegrouping selection module 114 further creates a fifth slice grouping forDST execution unit #5, which includes fifth encoded slices of each ofthe sets of encoded slices. As such, the fifth DST execution unitreceives encoded data slices corresponding to second error encodinginformation.

FIG. 10 is a diagram of an example of converting data 92 into slicegroups that expands on the preceding figures. As shown, the data 92 ispartitioned in accordance with a partitioning function 164 into aplurality of data partitions (1−x, where x is an integer greater than4). Each data partition (or chunkset of data) is encoded and groupedinto slice groupings as previously discussed by an encoding and groupingfunction 166. For a given data partition, the slice groupings are sentto distributed storage and task (DST) execution units. From datapartition to data partition, the ordering of the slice groupings to theDST execution units may vary.

For example, the slice groupings of data partition #1 is sent to the DSTexecution units such that the first DST execution receives first encodeddata slices of each of the sets of encoded data slices, whichcorresponds to a first continuous data chunk of the first data partition(e.g., refer to FIG. 9), a second DST execution receives second encodeddata slices of each of the sets of encoded data slices, whichcorresponds to a second continuous data chunk of the first datapartition, etc.

For the second data partition, the slice groupings may be sent to theDST execution units in a different order than it was done for the firstdata partition. For instance, the first slice grouping of the seconddata partition (e.g., slice group 2_(—)1) is sent to the second DSTexecution unit; the second slice grouping of the second data partition(e.g., slice group 2_(—)2) is sent to the third DST execution unit; thethird slice grouping of the second data partition (e.g., slice group2_(—)3) is sent to the fourth DST execution unit; the fourth slicegrouping of the second data partition (e.g., slice group 2_(—)4, whichincludes first error coding information) is sent to the fifth DSTexecution unit; and the fifth slice grouping of the second datapartition (e.g., slice group 2_(—)5, which includes second error codinginformation) is sent to the first DST execution unit.

The pattern of sending the slice groupings to the set of DST executionunits may vary in a predicted pattern, a random pattern, and/or acombination thereof from data partition to data partition. In addition,from data partition to data partition, the set of DST execution unitsmay change. For example, for the first data partition, DST executionunits 1-5 may be used; for the second data partition, DST executionunits 6-10 may be used; for the third data partition, DST executionunits 3-7 may be used; etc. As is also shown, the task is divided intopartial tasks that are sent to the DST execution units in conjunctionwith the slice groupings of the data partitions.

FIG. 11 is a schematic block diagram of an embodiment of a DST(distributed storage and/or task) execution unit that includes aninterface 169, a controller 86, memory 88, one or more DT (distributedtask) execution modules 90, and a DST client module 34. The memory 88 isof sufficient size to store a significant number of encoded data slices(e.g., thousands of slices to hundreds-of-millions of slices) and mayinclude one or more hard drives and/or one or more solid-state memorydevices (e.g., flash memory, DRAM, etc.).

In an example of storing a slice group, the DST execution modulereceives a slice grouping 96 (e.g., slice group #1) via interface 169.The slice grouping 96 includes, per partition, encoded data slices ofcontiguous data or encoded data slices of error coding (EC) data. Forslice group #1, the DST execution module receives encoded data slices ofcontiguous data for partitions #1 and #x (and potentially others between3 and x) and receives encoded data slices of EC data for partitions #2and #3 (and potentially others between 3 and x). Examples of encodeddata slices of contiguous data and encoded data slices of error coding(EC) data are discussed with reference to FIG. 9. The memory 88 storesthe encoded data slices of slice groupings 96 in accordance with memorycontrol information 174 it receives from the controller 86.

The controller 86 (e.g., a processing module, a CPU, etc.) generates thememory control information 174 based on a partial task(s) 98 anddistributed computing information (e.g., user information (e.g., userID, distributed computing permissions, data access permission, etc.),vault information (e.g., virtual memory assigned to user, user group,temporary storage for task processing, etc.), task validationinformation, etc.). For example, the controller 86 interprets thepartial task(s) 98 in light of the distributed computing information todetermine whether a requestor is authorized to perform the task 98, isauthorized to access the data, and/or is authorized to perform the taskon this particular data. When the requestor is authorized, thecontroller 86 determines, based on the task 98 and/or another input,whether the encoded data slices of the slice grouping 96 are to betemporarily stored or permanently stored. Based on the foregoing, thecontroller 86 generates the memory control information 174 to write theencoded data slices of the slice grouping 96 into the memory 88 and toindicate whether the slice grouping 96 is permanently stored ortemporarily stored.

With the slice grouping 96 stored in the memory 88, the controller 86facilitates execution of the partial task(s) 98. In an example, thecontroller 86 interprets the partial task 98 in light of thecapabilities of the DT execution module(s) 90. The capabilities includeone or more of MIPS capabilities, processing resources (e.g., quantityand capability of microprocessors, CPUs, digital signal processors,co-processor, microcontrollers, arithmetic logic circuitry, and/or andthe other analog and/or digital processing circuitry), availability ofthe processing resources, etc. If the controller 86 determines that theDT execution module(s) 90 have sufficient capabilities, it generatestask control information 176.

The task control information 176 may be a generic instruction (e.g.,perform the task on the stored slice grouping) or a series ofoperational codes. In the former instance, the DT execution module 90includes a co-processor function specifically configured (fixed orprogrammed) to perform the desired task 98. In the latter instance, theDT execution module 90 includes a general processor topology where thecontroller stores an algorithm corresponding to the particular task 98.In this instance, the controller 86 provides the operational codes(e.g., assembly language, source code of a programming language, objectcode, etc.) of the algorithm to the DT execution module 90 forexecution.

Depending on the nature of the task 98, the DT execution module 90 maygenerate intermediate partial results 102 that are stored in the memory88 or in a cache memory (not shown) within the DT execution module 90.In either case, when the DT execution module 90 completes execution ofthe partial task 98, it outputs one or more partial results 102. Thepartial results may 102 also be stored in memory 88.

If, when the controller 86 is interpreting whether capabilities of theDT execution module(s) 90 can support the partial task 98, thecontroller 86 determines that the DT execution module(s) 90 cannotadequately support the task 98 (e.g., does not have the right resources,does not have sufficient available resources, available resources wouldbe too slow, etc.), it then determines whether the partial task 98should be fully offloaded or partially offloaded.

If the controller 86 determines that the partial task 98 should be fullyoffloaded, it generates DST control information 178 and provides it tothe DST client module 34. The DST control information 178 includes thepartial task 98, memory storage information regarding the slice grouping96, and distribution instructions. The distribution instructionsinstruct the DST client module 34 to divide the partial task 98 intosub-partial tasks 172, to divide the slice grouping 96 into sub-slicegroupings 170, and identity of other DST execution units. The DST clientmodule 34 functions in a similar manner as the DST client module 34 ofFIGS. 3-10 to produce the sub-partial tasks 172 and the sub-slicegroupings 170 in accordance with the distribution instructions.

The DST client module 34 receives DST feedback 168 (e.g., sub-partialresults), via the interface 169, from the DST execution units to whichthe task was offloaded. The DST client module 34 provides thesub-partial results to the DST execution unit, which processes thesub-partial results to produce the partial result(s) 102.

If the controller 86 determines that the partial task 98 should bepartially offloaded, it determines what portion of the task 98 and/orslice grouping 96 should be processed locally and what should beoffloaded. For the portion that is being locally processed, thecontroller 86 generates task control information 176 as previouslydiscussed. For the portion that is being offloaded, the controller 86generates DST control information 178 as previously discussed.

When the DST client module 34 receives DST feedback 168 (e.g.,sub-partial results) from the DST executions units to which a portion ofthe task was offloaded, it provides the sub-partial results to the DTexecution module 90. The DT execution module 90 processes thesub-partial results with the sub-partial results it created to producethe partial result(s) 102.

The memory 88 may be further utilized to retrieve one or more of storedslices 100, stored results 104, partial results 102 when the DTexecution module 90 stores partial results 102 and/or results 104 andthe memory 88. For example, when the partial task 98 includes aretrieval request, the controller 86 outputs the memory control 174 tothe memory 88 to facilitate retrieval of slices 100 and/or results 104.

FIG. 12 is a schematic block diagram of an example of operation of adistributed storage and task (DST) execution unit storing encoded dataslices and executing a task thereon. To store the encoded data slices ofa partition 1 of slice grouping 1, a controller 86 generates writecommands as memory control information 174 such that the encoded slicesare stored in desired locations (e.g., permanent or temporary) withinmemory 88.

Once the encoded slices are stored, the controller 86 provides taskcontrol information 176 to a distributed task (DT) execution module 90.As a first step executing the task in accordance with the task controlinformation 176, the DT execution module 90 retrieves the encoded slicesfrom memory 88. The DT execution module 90 then reconstructs contiguousdata blocks of a data partition. As shown for this example,reconstructed contiguous data blocks of data partition 1 include datablocks 1-15 (e.g., d1-d15).

With the contiguous data blocks reconstructed, the DT execution module90 performs the task on the reconstructed contiguous data blocks. Forexample, the task may be to search the reconstructed contiguous datablocks for a particular word or phrase, identify where in thereconstructed contiguous data blocks the particular word or phraseoccurred, and/or count the occurrences of the particular word or phraseon the reconstructed contiguous data blocks. The DST execution unitcontinues in a similar manner for the encoded data slices of otherpartitions in slice grouping 1. Note that with using the unity matrixerror encoding scheme previously discussed, if the encoded data slicesof contiguous data are uncorrupted, the decoding of them is a relativelystraightforward process of extracting the data.

If, however, an encoded data slice of contiguous data is corrupted (ormissing), it can be rebuilt by accessing other DST execution units thatare storing the other encoded data slices of the set of encoded dataslices of the corrupted encoded data slice. In this instance, the DSTexecution unit having the corrupted encoded data slices retrieves atleast three encoded data slices (of contiguous data and of error codingdata) in the set from the other DST execution units (recall for thisexample, the pillar width is 5 and the decode threshold is 3). The DSTexecution unit decodes the retrieved data slices using the DS errorencoding parameters to recapture the corresponding data segment. The DSTexecution unit then re-encodes the data segment using the DS errorencoding parameters to rebuild the corrupted encoded data slice. Oncethe encoded data slice is rebuilt, the DST execution unit functions aspreviously described.

FIG. 13 is a schematic block diagram of an embodiment of an inbounddistributed storage and/or task (DST) processing section 82 of a DSTclient module coupled to DST execution units of a distributed storageand task network (DSTN) module via a network 24. The inbound DSTprocessing section 82 includes a de-grouping module 180, a DS (dispersedstorage) error decoding module 182, a data de-partitioning module 184, acontrol module 186, and a distributed task control module 188. Note thatthe control module 186 and/or the distributed task control module 188may be separate modules from corresponding ones of outbound DSTprocessing section or may be the same modules.

In an example of operation, the DST execution units have completedexecution of corresponding partial tasks on the corresponding slicegroupings to produce partial results 102. The inbounded DST processingsection 82 receives the partial results 102 via the distributed taskcontrol module 188. The inbound DST processing section 82 then processesthe partial results 102 to produce a final result, or results 104. Forexample, if the task was to find a specific word or phrase within data,the partial results 102 indicate where in each of the prescribedportions of the data the corresponding DST execution units found thespecific word or phrase. The distributed task control module 188combines the individual partial results 102 for the correspondingportions of the data into a final result 104 for the data as a whole.

In another example of operation, the inbound DST processing section 82is retrieving stored data from the DST execution units (i.e., the DSTNmodule). In this example, the DST execution units output encoded dataslices 100 corresponding to the data retrieval requests. The de-groupingmodule 180 receives retrieved slices 100 and de-groups them to produceencoded data slices per data partition 122. The DS error decoding module182 decodes, in accordance with DS error encoding parameters, theencoded data slices per data partition 122 to produce data partitions120.

The data de-partitioning module 184 combines the data partitions 120into the data 92. The control module 186 controls the conversion ofretrieve slices 100 into the data 92 using control signals 190 to eachof the modules. For instance, the control module 186 providesde-grouping information to the de-grouping module 180, provides the DSerror encoding parameters to the DS error decoding module 182, andprovides de-partitioning information to the data de-partitioning module184.

FIG. 14 is a logic diagram of an example of a method that is executableby distributed storage and task (DST) client module regarding inboundDST processing. The method begins at step 194 where the DST clientmodule receives partial results. The method continues at step 196 wherethe DST client module retrieves the task corresponding to the partialresults. For example, the partial results include header informationthat identifies the requesting entity, which correlates to the requestedtask.

The method continues at step 198 where the DST client module determinesresult processing information based on the task. For example, if thetask were to identify a particular word or phrase within the data, theresult processing information would indicate to aggregate the partialresults for the corresponding portions of the data to produce the finalresult. As another example, if the task were to count the occurrences ofa particular word or phrase within the data, results of processing theinformation would indicate to add the partial results to produce thefinal results. The method continues at step 200 where the DST clientmodule processes the partial results in accordance with the resultprocessing information to produce the final result or results.

FIG. 15 is a diagram of an example of de-grouping selection processingof an inbound distributed storage and task (DST) processing section of aDST client module. In general, this is an inverse process of thegrouping module of the outbound DST processing section of FIG. 9.Accordingly, for each data partition (e.g., partition #1), thede-grouping module retrieves the corresponding slice grouping from theDST execution units (EU) (e.g., DST 1-5).

As shown, DST execution unit #1 provides a first slice grouping, whichincludes the first encoded slices of each of the sets of encoded slices(e.g., encoded data slices of contiguous data of data blocks 1-15); DSTexecution unit #2 provides a second slice grouping, which includes thesecond encoded slices of each of the sets of encoded slices (e.g.,encoded data slices of contiguous data of data blocks 16-30); DSTexecution unit #3 provides a third slice grouping, which includes thethird encoded slices of each of the sets of encoded slices (e.g.,encoded data slices of contiguous data of data blocks 31-45); DSTexecution unit #4 provides a fourth slice grouping, which includes thefourth encoded slices of each of the sets of encoded slices (e.g., firstencoded data slices of error coding (EC) data); and DST execution unit#5 provides a fifth slice grouping, which includes the fifth encodedslices of each of the sets of encoded slices (e.g., first encoded dataslices of error coding (EC) data).

The de-grouping module de-groups the slice groupings (e.g., receivedslices 100) using a de-grouping selector 180 controlled by a controlsignal 190 as shown in the example to produce a plurality of sets ofencoded data slices (e.g., retrieved slices for a partition into sets ofslices 122). Each set corresponding to a data segment of the datapartition.

FIG. 16 is a schematic block diagram of an embodiment of a dispersedstorage (DS) error decoding module 182 of an inbound distributed storageand task (DST) processing section. The DS error decoding module 182includes an inverse per slice security processing module 202, ade-slicing module 204, an error decoding module 206, an inverse segmentsecurity module 208, a de-segmenting processing module 210, and acontrol module 186.

In an example of operation, the inverse per slice security processingmodule 202, when enabled by the control module 186, unsecures eachencoded data slice 122 based on slice de-security information receivedas control information 190 (e.g., the compliment of the slice securityinformation discussed with reference to FIG. 6) received from thecontrol module 186. The slice security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRCverification, etc.), and/or any other type of digital security. Forexample, when the inverse per slice security processing module 202 isenabled, it verifies integrity information (e.g., a CRC value) of eachencoded data slice 122, it decrypts each verified encoded data slice,and decompresses each decrypted encoded data slice to produce sliceencoded data 158. When the inverse per slice security processing module202 is not enabled, it passes the encoded data slices 122 as the slicedencoded data 158 or is bypassed such that the retrieved encoded dataslices 122 are provided as the sliced encoded data 158.

The de-slicing module 204 de-slices the sliced encoded data 158 intoencoded data segments 156 in accordance with a pillar width of the errorcorrection encoding parameters received as control information 190 fromthe control module 186. For example, if the pillar width is five, thede-slicing module 204 de-slices a set of five encoded data slices intoan encoded data segment 156. The error decoding module 206 decodes theencoded data segments 156 in accordance with error correction decodingparameters received as control information 190 from the control module186 to produce secure data segments 154. The error correction decodingparameters include identifying an error correction encoding scheme(e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an information dispersal algorithm, etc.), a pillar width, adecode threshold, a read threshold, a write threshold, etc. For example,the error correction decoding parameters identify a specific errorcorrection encoding scheme, specify a pillar width of five, and specifya decode threshold of three.

The inverse segment security processing module 208, when enabled by thecontrol module 186, unsecures the secured data segments 154 based onsegment security information received as control information 190 fromthe control module 186. The segment security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRC,etc.) verification, and/or any other type of digital security. Forexample, when the inverse segment security processing module 208 isenabled, it verifies integrity information (e.g., a CRC value) of eachsecure data segment 154, it decrypts each verified secured data segment,and decompresses each decrypted secure data segment to produce a datasegment 152. When the inverse segment security processing module 208 isnot enabled, it passes the decoded data segment 154 as the data segment152 or is bypassed.

The de-segment processing module 210 receives the data segments 152 andreceives de-segmenting information as control information 190 from thecontrol module 186. The de-segmenting information indicates how thede-segment processing module 210 is to de-segment the data segments 152into a data partition 120. For example, the de-segmenting informationindicates how the rows and columns of data segments are to be rearrangedto yield the data partition 120.

FIG. 17 is a diagram of an example of de-slicing and error decodingprocessing of a dispersed error decoding module. A de-slicing module 204receives at least a decode threshold number of encoded data slices 158for each data segment in accordance with control information 190 andprovides encoded data 156. In this example, a decode threshold is three.As such, each set of encoded data slices 158 is shown to have threeencoded data slices per data segment. The de-slicing module 204 mayreceive three encoded data slices per data segment because an associateddistributed storage and task (DST) client module requested retrievingonly three encoded data slices per segment or selected three of theretrieved encoded data slices per data segment. As shown, which is basedon the unity matrix encoding previously discussed with reference to FIG.8, an encoded data slice may be a data-based encoded data slice (e.g.,DS1_d1&d2) or an error code based encoded data slice (e.g., ES3_(—)1).

An error decoding module 206 decodes the encoded data 156 of each datasegment in accordance with the error correction decoding parameters ofcontrol information 190 to produce secured segments 154. In thisexample, data segment 1 includes 3 rows with each row being treated asone word for encoding. As such, data segment 1 includes three words:word 1 including data blocks d1 and d2, word 2 including data blocks d16and d17, and word 3 including data blocks d31 and d32. Each of datasegments 2-7 includes three words where each word includes two datablocks. Data segment 8 includes three words where each word includes asingle data block (e.g., d15, d30, and d45).

FIG. 18 is a diagram of an example of a de-segment processing of aninbound distributed storage and task (DST) processing. In this example,a de-segment processing module 210 receives data segments 152 (e.g.,1-8) and rearranges the data blocks of the data segments into rows andcolumns in accordance with de-segmenting information of controlinformation 190 to produce a data partition 120. Note that the number ofrows is based on the decode threshold (e.g., 3 in this specific example)and the number of columns is based on the number and size of the datablocks.

The de-segmenting module 210 converts the rows and columns of datablocks into the data partition 120. Note that each data block may be ofthe same size as other data blocks or of a different size. In addition,the size of each data block may be a few bytes to megabytes of data.

FIG. 19 is a diagram of an example of converting slice groups into data92 within an inbound distributed storage and task (DST) processingsection. As shown, the data 92 is reconstructed from a plurality of datapartitions (1−x, where x is an integer greater than 4). Each datapartition (or chunk set of data) is decoded and re-grouped using ade-grouping and decoding function 212 and a de-partition function 214from slice groupings as previously discussed. For a given datapartition, the slice groupings (e.g., at least a decode threshold perdata segment of encoded data slices) are received from DST executionunits. From data partition to data partition, the ordering of the slicegroupings received from the DST execution units may vary as discussedwith reference to FIG. 10.

FIG. 20 is a diagram of an example of a distributed storage and/orretrieval within the distributed computing system. The distributedcomputing system includes a plurality of distributed storage and/or task(DST) processing client modules 34 (one shown) coupled to a distributedstorage and/or task processing network (DSTN) module, or multiple DSTNmodules, via a network 24. The DST client module 34 includes an outboundDST processing section 80 and an inbound DST processing section 82. TheDSTN module includes a plurality of DST execution units. Each DSTexecution unit includes a controller 86, memory 88, one or moredistributed task (DT) execution modules 90, and a DST client module 34.

In an example of data storage, the DST client module 34 has data 92 thatit desires to store in the DSTN module. The data 92 may be a file (e.g.,video, audio, text, graphics, etc.), a data object, a data block, anupdate to a file, an update to a data block, etc. In this instance, theoutbound DST processing module 80 converts the data 92 into encoded dataslices 216 as will be further described with reference to FIGS. 21-23.The outbound DST processing module 80 sends, via the network 24, to theDST execution units for storage as further described with reference toFIG. 24.

In an example of data retrieval, the DST client module 34 issues aretrieve request to the DST execution units for the desired data 92. Theretrieve request may address each DST executions units storing encodeddata slices of the desired data, address a decode threshold number ofDST execution units, address a read threshold number of DST executionunits, or address some other number of DST execution units. In responseto the request, each addressed DST execution unit retrieves its encodeddata slices 100 of the desired data and sends them to the inbound DSTprocessing section 82, via the network 24.

When, for each data segment, the inbound DST processing section 82receives at least a decode threshold number of encoded data slices 100,it converts the encoded data slices 100 into a data segment. The inboundDST processing section 82 aggregates the data segments to produce theretrieved data 92.

FIG. 21 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing section 80 of a DSTclient module coupled to a distributed storage and task network (DSTN)module (e.g., a plurality of DST execution units) via a network 24. Theoutbound DST processing section 80 includes a data partitioning module110, a dispersed storage (DS) error encoding module 112, a groupselection module 114, a control module 116, and a distributed taskcontrol module 118.

In an example of operation, the data partitioning module 110 isby-passed such that data 92 is provided directly to the DS errorencoding module 112. The control module 116 coordinates the by-passingof the data partitioning module 110 by outputting a bypass 220 messageto the data partitioning module 110.

The DS error encoding module 112 receives the data 92 in a serialmanner, a parallel manner, and/or a combination thereof. The DS errorencoding module 112 DS error encodes the data in accordance with controlinformation 160 from the control module 116 to produce encoded dataslices 218. The DS error encoding includes segmenting the data 92 intodata segments, segment security processing (e.g., encryption,compression, watermarking, integrity check (e.g., CRC, etc.)), errorencoding, slicing, and/or per slice security processing (e.g.,encryption, compression, watermarking, integrity check (e.g., CRC,etc.)). The control information 160 indicates which steps of the DSerror encoding are active for the data 92 and, for active steps,indicates the parameters for the step. For example, the controlinformation 160 indicates that the error encoding is active and includeserror encoding parameters (e.g., pillar width, decode threshold, writethreshold, read threshold, type of error encoding, etc.).

The group selecting module 114 groups the encoded slices 218 of the datasegments into pillars of slices 216. The number of pillars correspondsto the pillar width of the DS error encoding parameters. In thisexample, the distributed task control module 118 facilitates the storagerequest.

FIG. 22 is a schematic block diagram of an example of a dispersedstorage (DS) error encoding module 112 for the example of FIG. 21. TheDS error encoding module 112 includes a segment processing module 142, asegment security processing module 144, an error encoding module 146, aslicing module 148, and a per slice security processing module 150. Eachof these modules is coupled to a control module 116 to receive controlinformation 160 therefrom.

In an example of operation, the segment processing module 142 receivesdata 92 and receives segmenting information as control information 160from the control module 116. The segmenting information indicates howthe segment processing module is to segment the data. For example, thesegmenting information indicates the size of each data segment. Thesegment processing module 142 segments the data 92 into data segments152 in accordance with the segmenting information.

The segment security processing module 144, when enabled by the controlmodule 116, secures the data segments 152 based on segment securityinformation received as control information 160 from the control module116. The segment security information includes data compression,encryption, watermarking, integrity check (e.g., CRC, etc.), and/or anyother type of digital security. For example, when the segment securityprocessing module 144 is enabled, it compresses a data segment 152,encrypts the compressed data segment, and generates a CRC value for theencrypted data segment to produce a secure data segment. When thesegment security processing module 144 is not enabled, it passes thedata segments 152 to the error encoding module 146 or is bypassed suchthat the data segments 152 are provided to the error encoding module146.

The error encoding module 146 encodes the secure data segments inaccordance with error correction encoding parameters received as controlinformation 160 from the control module 116. The error correctionencoding parameters include identifying an error correction encodingscheme (e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an information dispersal algorithm, etc.), a pillar width, adecode threshold, a read threshold, a write threshold, etc. For example,the error correction encoding parameters identify a specific errorcorrection encoding scheme, specifies a pillar width of five, andspecifies a decode threshold of three. From these parameters, the errorencoding module 146 encodes a data segment to produce an encoded datasegment.

The slicing module 148 slices the encoded data segment in accordancewith a pillar width of the error correction encoding parameters. Forexample, if the pillar width is five, the slicing module slices anencoded data segment into a set of five encoded data slices. As such,for a plurality of data segments, the slicing module 148 outputs aplurality of sets of encoded data slices as shown within encoding andslicing function 222 as described.

The per slice security processing module 150, when enabled by thecontrol module 116, secures each encoded data slice based on slicesecurity information received as control information 160 from thecontrol module 116. The slice security information includes datacompression, encryption, watermarking, integrity check (e.g., CRC,etc.), and/or any other type of digital security. For example, when theper slice security processing module 150 is enabled, it may compress anencoded data slice, encrypt the compressed encoded data slice, andgenerate a CRC value for the encrypted encoded data slice to produce asecure encoded data slice tweaking. When the per slice securityprocessing module 150 is not enabled, it passes the encoded data slicesor is bypassed such that the encoded data slices 218 are the output ofthe DS error encoding module 112.

FIG. 23 is a diagram of an example of converting data 92 into pillarslice groups utilizing encoding, slicing and pillar grouping function224 for storage in memory of a distributed storage and task network(DSTN) module. As previously discussed the data 92 is encoded and slicedinto a plurality of sets of encoded data slices; one set per datasegment. The grouping selection module organizes the sets of encodeddata slices into pillars of data slices. In this example, the DS errorencoding parameters include a pillar width of 5 and a decode thresholdof 3. As such, for each data segment, 5 encoded data slices are created.

The grouping selection module takes the first encoded data slice of eachof the sets and forms a first pillar, which may be sent to the first DSTexecution unit. Similarly, the grouping selection module creates thesecond pillar from the second slices of the sets; the third pillar fromthe third slices of the sets; the fourth pillar from the fourth slicesof the sets; and the fifth pillar from the fifth slices of the set.

FIG. 24 is a schematic block diagram of an embodiment of a distributedstorage and/or task (DST) execution unit that includes an interface 169,a controller 86, memory 88, one or more distributed task (DT) executionmodules 90, and a DST client module 34. A computing core 26 may beutilized to implement the one or more DT execution modules 90 and theDST client module 34. The memory 88 is of sufficient size to store asignificant number of encoded data slices (e.g., thousands of slices tohundreds-of-millions of slices) and may include one or more hard drivesand/or one or more solid-state memory devices (e.g., flash memory, DRAM,etc.).

In an example of storing a pillar of slices 216, the DST execution unitreceives, via interface 169, a pillar of slices 216 (e.g., pillar #1slices). The memory 88 stores the encoded data slices 216 of the pillarof slices in accordance with memory control information 174 it receivesfrom the controller 86. The controller 86 (e.g., a processing module, aCPU, etc.) generates the memory control information 174 based ondistributed storage information (e.g., user information (e.g., user ID,distributed storage permissions, data access permission, etc.), vaultinformation (e.g., virtual memory assigned to user, user group, etc.),etc.). Similarly, when retrieving slices, the DST execution unitreceives, via interface 169, a slice retrieval request. The memory 88retrieves the slice in accordance with memory control information 174 itreceives from the controller 86. The memory 88 outputs the slice 100,via the interface 169, to a requesting entity.

FIG. 25 is a schematic block diagram of an example of operation of aninbound distributed storage and/or task (DST) processing section 82 forretrieving dispersed error encoded data 92. The inbound DST processingsection 82 includes a de-grouping module 180, a dispersed storage (DS)error decoding module 182, a data de-partitioning module 184, a controlmodule 186, and a distributed task control module 188. Note that thecontrol module 186 and/or the distributed task control module 188 may beseparate modules from corresponding ones of an outbound DST processingsection or may be the same modules.

In an example of operation, the inbound DST processing section 82 isretrieving stored data 92 from the DST execution units (i.e., the DSTNmodule). In this example, the DST execution units output encoded dataslices corresponding to data retrieval requests from the distributedtask control module 188. The de-grouping module 180 receives pillars ofslices 100 and de-groups them in accordance with control information 190from the control module 186 to produce sets of encoded data slices 218.The DS error decoding module 182 decodes, in accordance with the DSerror encoding parameters received as control information 190 from thecontrol module 186, each set of encoded data slices 218 to produce datasegments, which are aggregated into retrieved data 92. The datade-partitioning module 184 is by-passed in this operational mode via abypass signal 226 of control information 190 from the control module186.

FIG. 26 is a schematic block diagram of an embodiment of a dispersedstorage (DS) error decoding module 182 of an inbound distributed storageand task (DST) processing section. The DS error decoding module 182includes an inverse per slice security processing module 202, ade-slicing module 204, an error decoding module 206, an inverse segmentsecurity module 208, and a de-segmenting processing module 210. Thedispersed error decoding module 182 is operable to de-slice and decodeencoded slices per data segment 218 utilizing a de-slicing and decodingfunction 228 to produce a plurality of data segments that arede-segmented utilizing a de-segment function 230 to recover data 92.

In an example of operation, the inverse per slice security processingmodule 202, when enabled by the control module 186 via controlinformation 190, unsecures each encoded data slice 218 based on slicede-security information (e.g., the compliment of the slice securityinformation discussed with reference to FIG. 6) received as controlinformation 190 from the control module 186. The slice de-securityinformation includes data decompression, decryption, de-watermarking,integrity check (e.g., CRC verification, etc.), and/or any other type ofdigital security. For example, when the inverse per slice securityprocessing module 202 is enabled, it verifies integrity information(e.g., a CRC value) of each encoded data slice 218, it decrypts eachverified encoded data slice, and decompresses each decrypted encodeddata slice to produce slice encoded data. When the inverse per slicesecurity processing module 202 is not enabled, it passes the encodeddata slices 218 as the sliced encoded data or is bypassed such that theretrieved encoded data slices 218 are provided as the sliced encodeddata.

The de-slicing module 204 de-slices the sliced encoded data into encodeddata segments in accordance with a pillar width of the error correctionencoding parameters received as control information 190 from a controlmodule 186. For example, if the pillar width is five, the de-slicingmodule de-slices a set of five encoded data slices into an encoded datasegment. Alternatively, the encoded data segment may include just threeencoded data slices (e.g., when the decode threshold is 3).

The error decoding module 206 decodes the encoded data segments inaccordance with error correction decoding parameters received as controlinformation 190 from the control module 186 to produce secure datasegments. The error correction decoding parameters include identifyingan error correction encoding scheme (e.g., forward error correctionalgorithm, a Reed-Solomon based algorithm, an information dispersalalgorithm, etc.), a pillar width, a decode threshold, a read threshold,a write threshold, etc. For example, the error correction decodingparameters identify a specific error correction encoding scheme, specifya pillar width of five, and specify a decode threshold of three.

The inverse segment security processing module 208, when enabled by thecontrol module 186, unsecures the secured data segments based on segmentsecurity information received as control information 190 from thecontrol module 186. The segment security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRC,etc.) verification, and/or any other type of digital security. Forexample, when the inverse segment security processing module is enabled,it verifies integrity information (e.g., a CRC value) of each securedata segment, it decrypts each verified secured data segment, anddecompresses each decrypted secure data segment to produce a datasegment 152. When the inverse segment security processing module 208 isnot enabled, it passes the decoded data segment 152 as the data segmentor is bypassed. The de-segmenting processing module 210 aggregates thedata segments 152 into the data 92 in accordance with controlinformation 190 from the control module 186.

FIG. 27 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module that includes aplurality of distributed storage and task (DST) execution units (#1through #n, where, for example, n is an integer greater than or equal tothree). Each of the DST execution units includes a DST client module 34,a controller 86, one or more DT (distributed task) execution modules 90,and memory 88.

In this example, the DSTN module stores, in the memory of the DSTexecution units, a plurality of DS (dispersed storage) encoded data(e.g., 1 through n, where n is an integer greater than or equal to two)and stores a plurality of DS encoded task codes (e.g., 1 through k,where k is an integer greater than or equal to two). The DS encoded datamay be encoded in accordance with one or more examples described withreference to FIGS. 3-19 (e.g., organized in slice groupings) or encodedin accordance with one or more examples described with reference toFIGS. 20-26 (e.g., organized in pillar groups). The data that is encodedinto the DS encoded data may be of any size and/or of any content. Forexample, the data may be one or more digital books, a copy of acompany's emails, a large-scale Internet search, a video security file,one or more entertainment video files (e.g., television programs,movies, etc.), data files, and/or any other large amount of data (e.g.,greater than a few Terra-Bytes).

The tasks that are encoded into the DS encoded task code may be a simplefunction (e.g., a mathematical function, a logic function, an identifyfunction, a find function, a search engine function, a replace function,etc.), a complex function (e.g., compression, human and/or computerlanguage translation, text-to-voice conversion, voice-to-textconversion, etc.), multiple simple and/or complex functions, one or morealgorithms, one or more applications, etc. The tasks may be encoded intothe DS encoded task code in accordance with one or more examplesdescribed with reference to FIGS. 3-19 (e.g., organized in slicegroupings) or encoded in accordance with one or more examples describedwith reference to FIGS. 20-26 (e.g., organized in pillar groups).

In an example of operation, a DST client module of a user device or of aDST processing unit issues a DST request to the DSTN module. The DSTrequest may include a request to retrieve stored data, or a portionthereof, may include a request to store data that is included with theDST request, may include a request to perform one or more tasks onstored data, may include a request to perform one or more tasks on dataincluded with the DST request, etc. In the cases where the DST requestincludes a request to store data or to retrieve data, the client moduleand/or the DSTN module processes the request as previously discussedwith reference to one or more of FIGS. 3-19 (e.g., slice groupings)and/or 20-26 (e.g., pillar groupings). In the case where the DST requestincludes a request to perform one or more tasks on data included withthe DST request, the DST client module and/or the DSTN module processthe DST request as previously discussed with reference to one or more ofFIGS. 3-19.

In the case where the DST request includes a request to perform one ormore tasks on stored data, the DST client module and/or the DSTN moduleprocesses the DST request as will be described with reference to one ormore of FIGS. 28-39. In general, the DST client module identifies dataand one or more tasks for the DSTN module to execute upon the identifieddata. The DST request may be for a one-time execution of the task or foran on-going execution of the task. As an example of the latter, as acompany generates daily emails, the DST request may be to daily searchnew emails for inappropriate content and, if found, record the content,the email sender(s), the email recipient(s), email routing information,notify human resources of the identified email, etc.

FIG. 28 is a schematic block diagram of an example of a distributedcomputing system performing tasks on stored data. In this example, twodistributed storage and task (DST) client modules 1-2 are shown: thefirst may be associated with a user device and the second may beassociated with a DST processing unit or a high priority user device(e.g., high priority clearance user, system administrator, etc.). EachDST client module includes a list of stored data 234 and a list of taskscodes 236. The list of stored data 234 includes one or more entries ofdata identifying information, where each entry identifies data stored inthe DSTN module 22. The data identifying information (e.g., data ID)includes one or more of a data file name, a data file directory listing,DSTN addressing information of the data, a data object identifier, etc.The list of tasks 236 includes one or more entries of task codeidentifying information, when each entry identifies task codes stored inthe DSTN module 22. The task code identifying information (e.g., taskID) includes one or more of a task file name, a task file directorylisting, DSTN addressing information of the task, another type ofidentifier to identify the task, etc.

As shown, the list of data 234 and the list of tasks 236 are eachsmaller in number of entries for the first DST client module than thecorresponding lists of the second DST client module. This may occurbecause the user device associated with the first DST client module hasfewer privileges in the distributed computing system than the deviceassociated with the second DST client module. Alternatively, this mayoccur because the user device associated with the first DST clientmodule serves fewer users than the device associated with the second DSTclient module and is restricted by the distributed computing systemaccordingly. As yet another alternative, this may occur through norestraints by the distributed computing system, it just occurred becausethe operator of the user device associated with the first DST clientmodule has selected fewer data and/or fewer tasks than the operator ofthe device associated with the second DST client module.

In an example of operation, the first DST client module selects one ormore data entries 238 and one or more tasks 240 from its respectivelists (e.g., selected data ID and selected task ID). The first DSTclient module sends its selections to a task distribution module 232.The task distribution module 232 may be within a stand-alone device ofthe distributed computing system, may be within the user device thatcontains the first DST client module, or may be within the DSTN module22.

Regardless of the task distributions modules location, it generates DSTallocation information 242 from the selected task ID 240 and theselected data ID 238. The DST allocation information 242 includes datapartitioning information, task execution information, and/orintermediate result information. The task distribution module 232 sendsthe DST allocation information 242 to the DSTN module 22. Note that oneor more examples of the DST allocation information will be discussedwith reference to one or more of FIGS. 29-39.

The DSTN module 22 interprets the DST allocation information 242 toidentify the stored DS encoded data (e.g., DS error encoded data 2) andto identify the stored DS error encoded task code (e.g., DS errorencoded task code 1). In addition, the DSTN module 22 interprets the DSTallocation information 242 to determine how the data is to bepartitioned and how the task is to be partitioned. The DSTN module 22also determines whether the selected DS error encoded data 238 needs tobe converted from pillar grouping to slice grouping. If so, the DSTNmodule 22 converts the selected DS error encoded data into slicegroupings and stores the slice grouping DS error encoded data byoverwriting the pillar grouping DS error encoded data or by storing itin a different location in the memory of the DSTN module 22 (i.e., doesnot overwrite the pillar grouping DS encoded data).

The DSTN module 22 partitions the data and the task as indicated in theDST allocation information 242 and sends the portions to selected DSTexecution units of the DSTN module 22. Each of the selected DSTexecution units performs its partial task(s) on its slice groupings toproduce partial results. The DSTN module 22 collects the partial resultsfrom the selected DST execution units and provides them, as resultinformation 244, to the task distribution module. The result information244 may be the collected partial results, one or more final results asproduced by the DSTN module 22 from processing the partial results inaccordance with the DST allocation information 242, or one or moreintermediate results as produced by the DSTN module 22 from processingthe partial results in accordance with the DST allocation information242.

The task distribution module 232 receives the result information 244 andprovides one or more final results 104 therefrom to the first DST clientmodule. The final result(s) 104 may be result information 244 or aresult(s) of the task distribution module's processing of the resultinformation 244.

In concurrence with processing the selected task of the first DST clientmodule, the distributed computing system may process the selectedtask(s) of the second DST client module on the selected data(s) of thesecond DST client module. Alternatively, the distributed computingsystem may process the second DST client module's request subsequent to,or preceding, that of the first DST client module. Regardless of theordering and/or parallel processing of the DST client module requests,the second DST client module provides its selected data 238 and selectedtask 240 to a task distribution module 232. If the task distributionmodule 232 is a separate device of the distributed computing system orwithin the DSTN module, the task distribution modules 232 coupled to thefirst and second DST client modules may be the same module. The taskdistribution module 232 processes the request of the second DST clientmodule in a similar manner as it processed the request of the first DSTclient module.

FIG. 29 is a schematic block diagram of an embodiment of a taskdistribution module 232 facilitating the example of FIG. 28. The taskdistribution module 232 includes a plurality of tables it uses togenerate distributed storage and task (DST) allocation information 242for selected data and selected tasks received from a DST client module.The tables include data storage information 248, task storageinformation 250, distributed task (DT) execution module information 252,and task

sub-task mapping information 246.

The data storage information table 248 includes a data identification(ID) field 260, a data size field 262, an addressing information field264, distributed storage (DS) information 266, and may further includeother information regarding the data, how it is stored, and/or how itcan be processed. For example, DS encoded data #1 has a data ID of 1, adata size of AA (e.g., a byte size of a few terra-bytes or more),addressing information of Addr_(—)1_AA, and DS parameters of ⅗;SEG_(—)1; and SLC_(—)1. In this example, the addressing information maybe a virtual address corresponding to the virtual address of the firststorage word (e.g., one or more bytes) of the data and information onhow to calculate the other addresses, may be a range of virtualaddresses for the storage words of the data, physical addresses of thefirst storage word or the storage words of the data, may be a list ofslice names of the encoded data slices of the data, etc. The DSparameters may include identity of an error encoding scheme, decodethreshold/pillar width (e.g., ⅗ for the first data entry), segmentsecurity information (e.g., SEG_(—)1), per slice security information(e.g., SLC_(—)1), and/or any other information regarding how the datawas encoded into data slices.

The task storage information table 250 includes a task identification(ID) field 268, a task size field 270, an addressing information field272, distributed storage (DS) information 274, and may further includeother information regarding the task, how it is stored, and/or how itcan be used to process data. For example, DS encoded task #2 has a taskID of 2, a task size of XY, addressing information of Addr_(—)2_XY, andDS parameters of ⅗; SEG_(—)2; and SLC_(—)2. In this example, theaddressing information may be a virtual address corresponding to thevirtual address of the first storage word (e.g., one or more bytes) ofthe task and information on how to calculate the other addresses, may bea range of virtual addresses for the storage words of the task, physicaladdresses of the first storage word or the storage words of the task,may be a list of slices names of the encoded slices of the task code,etc. The DS parameters may include identity of an error encoding scheme,decode threshold/pillar width (e.g., ⅗ for the first data entry),segment security information (e.g., SEG_(—)2), per slice securityinformation (e.g., SLC_(—)2), and/or any other information regarding howthe task was encoded into encoded task slices. Note that the segmentand/or the per-slice security information include a type of encryption(if enabled), a type of compression (if enabled), watermarkinginformation (if enabled), and/or an integrity check scheme (if enabled).

The task

sub-task mapping information table 246 includes a task field 256 and asub-task field 258. The task field 256 identifies a task stored in thememory of a distributed storage and task network (DSTN) module and thecorresponding sub-task fields 258 indicates whether the task includessub-tasks and, if so, how many and if any of the sub-tasks are ordered.In this example, the task

sub-task mapping information table 246 includes an entry for each taskstored in memory of the DSTN module (e.g., task 1 through task k). Inparticular, this example indicates that task 1 includes 7 sub-tasks;task 2 does not include sub-tasks, and task k includes r number ofsub-tasks (where r is an integer greater than or equal to two).

The DT execution module table 252 includes a DST execution unit ID field276, a DT execution module ID field 278, and a DT execution modulecapabilities field 280. The DST execution unit ID field 276 includes theidentity of DST units in the DSTN module. The DT execution module IDfield 278 includes the identity of each DT execution unit in each DSTunit. For example, DST unit 1 includes three DT executions modules(e.g., 1_(—)1, 1_(—)2, and 1_(—)3). The DT execution capabilities field280 includes identity of the capabilities of the corresponding DTexecution unit. For example, DT execution module 1 _(—)1 includescapabilities X, where X includes one or more of MIPS capabilities,processing resources (e.g., quantity and capability of microprocessors,CPUs, digital signal processors, co-processor, microcontrollers,arithmetic logic circuitry, and/or and other analog and/or digitalprocessing circuitry), availability of the processing resources, memoryinformation (e.g., type, size, availability, etc.), and/or anyinformation germane to executing one or more tasks.

From these tables, the task distribution module 232 generates the DSTallocation information 242 to indicate where the data is stored, how topartition the data, where the task is stored, how to partition the task,which DT execution units should perform which partial task on which datapartitions, where and how intermediate results are to be stored, etc. Ifmultiple tasks are being performed on the same data or different data,the task distribution module factors such information into itsgeneration of the DST allocation information.

FIG. 30 is a diagram of a specific example of a distributed computingsystem performing tasks on stored data as a task flow 318. In thisexample, selected data 92 is data 2 and selected tasks are tasks 1, 2,and 3. Task 1 corresponds to analyzing translation of data from onelanguage to another (e.g., human language or computer language); task 2corresponds to finding specific words and/or phrases in the data; andtask 3 corresponds to finding specific translated words or/or phrases intranslated data.

In this example, task 1 includes 7 sub-tasks: task 1_(—)1—identifynon-words (non-ordered); task 1_(—)2—identify unique words(non-ordered); task 1_(—)3—translate (non-ordered); task1_(—)4—translate back (ordered after task 1_(—)3); task 1_(—)5—compareto ID errors (ordered after task 1-4); task 1_(—)6—determine non-wordtranslation errors (ordered after task 1_(—)5 and 1_(—)1); and task1_(—)7—determine correct translations (ordered after 1_(—)5 and 1_(—)2).The sub-task further indicates whether they are an ordered task (i.e.,are dependent on the outcome of another task) or non-order (i.e., areindependent of the outcome of another task). Task 2 does not includesub-tasks and task 3 includes two sub-tasks: task 3_(—)1 translate; andtask 3_(—)2 find specific word or phrase in translated data.

In general, the three tasks collectively are selected to analyze datafor translation accuracies, translation errors, translation anomalies,occurrence of specific words or phrases in the data, and occurrence ofspecific words or phrases on the translated data. Graphically, the data92 is translated 306 into translated data 282; is analyzed for specificwords and/or phrases 300 to produce a list of specific words and/orphrases 286; is analyzed for non-words 302 (e.g., not in a referencedictionary) to produce a list of non-words 290; and is analyzed forunique words 316 included in the data 92 (i.e., how many different wordsare included in the data) to produce a list of unique words 298. Each ofthese tasks is independent of each other and can therefore be processedin parallel if desired.

The translated data 282 is analyzed (e.g., sub-task 3_(—)2) for specifictranslated words and/or phrases 304 to produce a list of specifictranslated words and/or phrases. The translated data 282 is translatedback 308 (e.g., sub-task 1_(—)4) into the language of the original datato produce re-translated data 284. These two tasks are dependent on thetranslate task (e.g., task 1_(—)3) and thus must be ordered after thetranslation task, which may be in a pipelined ordering or a serialordering. The re-translated data 284 is then compared 310 with theoriginal data 92 to find words and/or phrases that did not translate(one way and/or the other) properly to produce a list of incorrectlytranslated words 294. As such, the comparing task (e.g., sub-task1_(—)5) 310 is ordered after the translation 306 and re-translationtasks 308 (e.g., sub-tasks 1_(—)3 and 1_(—)4).

The list of words incorrectly translated 294 is compared 312 to the listof non-words 290 to identify words that were not properly translatedbecause the words are non-words to produce a list of errors due tonon-words 292. In addition, the list of words incorrectly translated 294is compared 314 to the list of unique words 298 to identify unique wordsthat were properly translated to produce a list of correctly translatedwords 296. The comparison may also identify unique words that were notproperly translated to produce a list of unique words that were notproperly translated. Note that each list of words (e.g., specific wordsand/or phrases, non-words, unique words, translated words and/orphrases, etc.,) may include the word and/or phrase, how many times it isused, where in the data it is used, and/or any other informationrequested regarding a word and/or phrase.

FIG. 31 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing data and taskcodes for the example of FIG. 30. As shown, DS encoded data 2 is storedas encoded data slices across the memory (e.g., stored in memories 88)of DST execution units 1-5; the DS encoded task code 1 (of task 1) andDS encoded task 3 are stored as encoded task slices across the memory ofDST execution units 1-5; and DS encoded task code 2 (of task 2) isstored as encoded task slices across the memory of DST execution units3-7. As indicated in the data storage information table and the taskstorage information table of FIG. 29, the respective data/task has DSparameters of ⅗ for their decode threshold/pillar width; hence spanningthe memory of five DST execution units.

FIG. 32 is a diagram of an example of distributed storage and task (DST)allocation information 242 for the example of FIG. 30. The DSTallocation information 242 includes data partitioning information 320,task execution information 322, and intermediate result information 324.The data partitioning information 320 includes the data identifier (ID),the number of partitions to split the data into, address information foreach data partition, and whether the DS encoded data has to betransformed from pillar grouping to slice grouping. The task executioninformation 322 includes tabular information having a taskidentification field 326, a task ordering field 328, a data partitionfield ID 330, and a set of DT execution modules 332 to use for thedistributed task processing per data partition. The intermediate resultinformation 324 includes tabular information having a name ID field 334,an ID of the DST execution unit assigned to process the correspondingintermediate result 336, a scratch pad storage field 338, and anintermediate result storage field 340.

Continuing with the example of FIG. 30, where tasks 1-3 are to bedistributedly performed on data 2, the data partitioning informationincludes the ID of data 2. In addition, the task distribution moduledetermines whether the DS encoded data 2 is in the proper format fordistributed computing (e.g., was stored as slice groupings). If not, thetask distribution module indicates that the DS encoded data 2 formatneeds to be changed from the pillar grouping format to the slicegrouping format, which will be done the by DSTN module. In addition, thetask distribution module determines the number of partitions to dividethe data into (e.g., 2_(—)1 through 2_z) and addressing information foreach partition.

The task distribution module generates an entry in the task executioninformation section for each sub-task to be performed. For example, task1_(—)1 (e.g., identify non-words on the data) has no task ordering(i.e., is independent of the results of other sub-tasks), is to beperformed on data partitions 2_(—)1 through 2_z by DT execution modules1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1. For instance, DT executionmodules 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 search for non-wordsin data partitions 2_(—)1 through 2_z to produce task 1_(—)1intermediate results (R1-1, which is a list of non-words). Task 1_(—)2(e.g., identify unique words) has similar task execution information astask 1_(—)1 to produce task 1_(—)2 intermediate results (R1-2, which isthe list of unique words).

Task 1_(—)3 (e.g., translate) includes task execution information asbeing non-ordered (i.e., is independent), having DT execution modules1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 translate data partitions2_(—)1 through 2_(—)4 and having DT execution modules 1_(—)2, 2_(—)2,3_(—)2, 4_(—)2, and 5_(—)2 translate data partitions 2_(—)5 through 2_zto produce task 1_(—)3 intermediate results (R1-3, which is thetranslated data). In this example, the data partitions are grouped,where different sets of DT execution modules perform a distributedsub-task (or task) on each data partition group, which allows forfurther parallel processing.

Task 1_(—)4 (e.g., translate back) is ordered after task 1_(—)3 and isto be executed on task 1_(—)3's intermediate result (e.g., R1-3_(—)1)(e.g., the translated data). DT execution modules 1_(—)1, 2_(—)1,3_(—)1, 4_(—)1, and 5_(—)1 are allocated to translate back task 1_(—)3intermediate result partitions R1-3_(—)1 through R1-3_(—)4 and DTexecution modules 1_(—)2, 2_(—)2, 6_(—)1, 7_(—)1, and 7_(—)2 areallocated to translate back task 1_(—)3 intermediate result partitionsR1-3_(—)5 through R1-3_z to produce task 1-4 intermediate results (R1-4,which is the translated back data).

Task 1_(—)5 (e.g., compare data and translated data to identifytranslation errors) is ordered after task 1_(—)4 and is to be executedon task 1_(—)4's intermediate results (R4-1) and on the data. DTexecution modules 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 areallocated to compare the data partitions (2_(—)1 through 2_z) withpartitions of task 1-4 intermediate results partitions R1-4_(—)1 throughR1-4_z to produce task 1_(—)5 intermediate results (R1-5, which is thelist words translated incorrectly).

Task 1_(—)6 (e.g., determine non-word translation errors) is orderedafter tasks 1_(—)1 and 1_(—)5 and is to be executed on tasks 1_(—)1'sand 1_(—)5's intermediate results (R1-1 and R1-5). DT execution modules1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 are allocated to compare thepartitions of task 1_(—)1 intermediate results (R1-1_(—)1 throughR1-1_z) with partitions of task 1-5 intermediate results partitions(R1-5_(—)1 through R1-5_z) to produce task 1_(—)6 intermediate results(R1-6, which is the list translation errors due to non-words).

Task 1_(—)7 (e.g., determine words correctly translated) is orderedafter tasks 1_(—)2 and 1_(—)5 and is to be executed on tasks 1_(—)2'sand 1_(—)5's intermediate results (R1-1 and R1-5). DT execution modules1_(—)2, 2_(—)2, 3_(—)2, 4_(—)2, and 5_(—)2 are allocated to compare thepartitions of task 1_(—)2 intermediate results (R1-2_(—)1 throughR1-2_z) with partitions of task 1-5 intermediate results partitions(R1-5_(—)1 through R1-5_z) to produce task 1_(—)7 intermediate results(R1-7, which is the list of correctly translated words).

Task 2 (e.g., find specific words and/or phrases) has no task ordering(i.e., is independent of the results of other sub-tasks), is to beperformed on data partitions 2_(—)1 through 2_z by DT execution modules3_(—)1, 4_(—)1, 5_(—)1, 6_(—)1, and 7_(—)1. For instance, DT executionmodules 3_(—)1, 4_(—)1, 5_(—)1, 6_(—)1, and 7_(—)1 search for specificwords and/or phrases in data partitions 2_(—)1 through 2_z to producetask 2 intermediate results (R2, which is a list of specific wordsand/or phrases).

Task 3_(—)2 (e.g., find specific translated words and/or phrases) isordered after task 1_(—)3 (e.g., translate) is to be performed onpartitions R1-3_(—)1 through R1-3_z by DT execution modules 1_(—)2,2_(—)2, 3_(—)2, 4_(—)2, and 5_(—)2. For instance, DT execution modules1_(—)2, 2_(—)2, 3_(—)2, 4_(—)2, and 5_(—)2 search for specifictranslated words and/or phrases in the partitions of the translated data(R1-3_(—)1 through R1-3_z) to produce task 3_(—)2 intermediate results(R3-2, which is a list of specific translated words and/or phrases).

For each task, the intermediate result information indicates which DSTunit is responsible for overseeing execution of the task and, if needed,processing the partial results generated by the set of allocated DTexecution units. In addition, the intermediate result informationindicates a scratch pad memory for the task and where the correspondingintermediate results are to be stored. For example, for intermediateresult R1-1 (the intermediate result of task 1_(—)1), DST unit 1 isresponsible for overseeing execution of the task 1_(—)1 and coordinatesstorage of the intermediate result as encoded intermediate result slicesstored in memory of DST execution units 1-5. In general, the scratch padis for storing non-DS encoded intermediate results and the intermediateresult storage is for storing DS encoded intermediate results.

FIGS. 33-38 are schematic block diagrams of the distributed storage andtask network (DSTN) module performing the example of FIG. 30. In FIG.33, the DSTN module accesses the data 92 and partitions it into aplurality of partitions 1-z in accordance with distributed storage andtask network (DST) allocation information. For each data partition, theDSTN identifies a set of its DT (distributed task) execution modules 90to perform the task (e.g., identify non-words (i.e., not in a referencedictionary) within the data partition) in accordance with the DSTallocation information. From data partition to data partition, the setof DT execution modules 90 may be the same, different, or a combinationthereof (e.g., some data partitions use the same set while other datapartitions use different sets).

For the first data partition, the first set of DT execution modules(e.g., 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 per the DST allocationinformation of FIG. 32) executes task 1_(—)1 to produce a first partialresult 102 of non-words found in the first data partition. The secondset of DT execution modules (e.g., 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and5_(—)1 per the DST allocation information of FIG. 32) executes task1_(—)1 to produce a second partial result 102 of non-words found in thesecond data partition. The sets of DT execution modules (as per the DSTallocation information) perform task 1_(—)1 on the data partitions untilthe “z” set of DT execution modules performs task 1_(—)1 on the “zth”data partition to produce a “zth” partial result 102 of non-words foundin the “zth” data partition.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results toproduce the first intermediate result (R1-1), which is a list ofnon-words found in the data. For instance, each set of DT executionmodules 90 stores its respective partial result in the scratchpad memoryof DST execution unit 1 (which is identified in the DST allocation ormay be determined by DST execution unit 1). A processing module of DSTexecution 1 is engaged to aggregate the first through “zth” partialresults to produce the first intermediate result (e.g., R1_(—)1). Theprocessing module stores the first intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the first intermediate result (e.g., the list ofnon-words). To begin the encoding, the DST client module determineswhether the list of non-words is of a sufficient size to partition(e.g., greater than a Terra-Byte). If yes, it partitions the firstintermediate result (R1-1) into a plurality of partitions (e.g.,R1-1_(—)1 through R1-1_m). If the first intermediate result is not ofsufficient size to partition, it is not partitioned.

For each partition of the first intermediate result, or for the firstintermediate result, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes ⅗decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-5).

In FIG. 34, the DSTN module is performing task 1_(—)2 (e.g., find uniquewords) on the data 92. To begin, the DSTN module accesses the data 92and partitions it into a plurality of partitions 1-z in accordance withthe DST allocation information or it may use the data partitions of task1_(—)1 if the partitioning is the same. For each data partition, theDSTN identifies a set of its DT execution modules to perform task 1_(—)2in accordance with the DST allocation information. From data partitionto data partition, the set of DT execution modules may be the same,different, or a combination thereof. For the data partitions, theallocated set of DT execution modules executes task 1_(—)2 to produce apartial results (e.g., 1^(st) through “zth”) of unique words found inthe data partitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results102 of task 1_(—)2 to produce the second intermediate result (R1-2),which is a list of unique words found in the data 92. The processingmodule of DST execution 1 is engaged to aggregate the first through“zth” partial results of unique words to produce the second intermediateresult. The processing module stores the second intermediate result asnon-DS error encoded data in the scratchpad memory or in another sectionof memory of DST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the second intermediate result (e.g., the list ofnon-words). To begin the encoding, the DST client module determineswhether the list of unique words is of a sufficient size to partition(e.g., greater than a Terra-Byte). If yes, it partitions the secondintermediate result (R1-2) into a plurality of partitions (e.g.,R1-2_(—)1 through R1-2_m). If the second intermediate result is not ofsufficient size to partition, it is not partitioned.

For each partition of the second intermediate result, or for the secondintermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes ⅗decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-5).

In FIG. 35, the DSTN module is performing task 1_(—)3 (e.g., translate)on the data 92. To begin, the DSTN module accesses the data 92 andpartitions it into a plurality of partitions 1-z in accordance with theDST allocation information or it may use the data partitions of task1_(—)1 if the partitioning is the same. For each data partition, theDSTN identifies a set of its DT execution modules to perform task 1_(—)3in accordance with the DST allocation information (e.g., DT executionmodules 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 translate datapartitions 2_(—)1 through 2_(—)4 and DT execution modules 1_(—)2,2_(—)2, 3_(—)2, 4_(—)2, and 5_(—)2 translate data partitions 2_(—)5through 2_z). For the data partitions, the allocated set of DT executionmodules 90 executes task 1_(—)3 to produce partial results 102 (e.g.,1^(st) through “zth”) of translated data.

As indicated in the DST allocation information of FIG. 32, DST executionunit 2 is assigned to process the first through “zth” partial results oftask 1_(—)3 to produce the third intermediate result (R1-3), which istranslated data. The processing module of DST execution 2 is engaged toaggregate the first through “zth” partial results of translated data toproduce the third intermediate result. The processing module stores thethird intermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 2.

DST execution unit 2 engages its DST client module to slice groupingbased DS error encode the third intermediate result (e.g., translateddata). To begin the encoding, the DST client module partitions the thirdintermediate result (R1-3) into a plurality of partitions (e.g.,R1-3_(—)1 through R1-3_y). For each partition of the third intermediateresult, the DST client module uses the DS error encoding parameters ofthe data (e.g., DS parameters of data 2, which includes ⅗ decodethreshold/pillar width ratio) to produce slice groupings. The slicegroupings are stored in the intermediate result memory (e.g., allocatedmemory in the memories of DST execution units 2-6 per the DST allocationinformation).

As is further shown in FIG. 35, the DSTN module is performing task1_(—)4 (e.g., retranslate) on the translated data of the thirdintermediate result. To begin, the DSTN module accesses the translateddata (from the scratchpad memory or from the intermediate result memoryand decodes it) and partitions it into a plurality of partitions inaccordance with the DST allocation information. For each partition ofthe third intermediate result, the DSTN identifies a set of its DTexecution modules 90 to perform task 1_(—)4 in accordance with the DSTallocation information (e.g., DT execution modules 1_(—)1, 2_(—)1,3_(—)1, 4_(—)1, and 5_(—)1 are allocated to translate back partitionsR1-3_(—)1 through R1-3_(—)4 and DT execution modules 1_(—)2, 2_(—)2,6_(—)1, 7_(—)1, and 7_(—)2 are allocated to translate back partitionsR1-3_(—)5 through R1-3_z). For the partitions, the allocated set of DTexecution modules executes task 1_(—)4 to produce partial results 102(e.g., 1^(st) through “zth”) of re-translated data.

As indicated in the DST allocation information of FIG. 32, DST executionunit 3 is assigned to process the first through “zth” partial results oftask 1_(—)4 to produce the fourth intermediate result (R1-4), which isretranslated data. The processing module of DST execution 3 is engagedto aggregate the first through “zth” partial results of retranslateddata to produce the fourth intermediate result. The processing modulestores the fourth intermediate result as non-DS error encoded data inthe scratchpad memory or in another section of memory of DST executionunit 3.

DST execution unit 3 engages its DST client module to slice groupingbased DS error encode the fourth intermediate result (e.g., retranslateddata). To begin the encoding, the DST client module partitions thefourth intermediate result (R1-4) into a plurality of partitions (e.g.,R1-4_(—)1 through R1-4_z). For each partition of the fourth intermediateresult, the DST client module uses the DS error encoding parameters ofthe data (e.g., DS parameters of data 2, which includes ⅗ decodethreshold/pillar width ratio) to produce slice groupings. The slicegroupings are stored in the intermediate result memory (e.g., allocatedmemory in the memories of DST execution units 3-7 per the DST allocationinformation).

In FIG. 36, a distributed storage and task network (DSTN) module isperforming task 1_(—)5 (e.g., compare) on data 92 and retranslated dataof FIG. 35. To begin, the DSTN module accesses the data 92 andpartitions it into a plurality of partitions in accordance with the DSTallocation information or it may use the data partitions of task 1_(—)1if the partitioning is the same. The DSTN module also accesses theretranslated data from the scratchpad memory, or from the intermediateresult memory and decodes it, and partitions it into a plurality ofpartitions in accordance with the DST allocation information. The numberof partitions of the retranslated data corresponds to the number ofpartitions of the data.

For each pair of partitions (e.g., data partition 1 and retranslateddata partition 1), the DSTN identifies a set of its DT execution modules90 to perform task 1_(—)5 in accordance with the DST allocationinformation (e.g., DT execution modules 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1,and 5_(—)1). For each pair of partitions, the allocated set of DTexecution modules executes task 1_(—)5 to produce partial results 102(e.g., 1^(st) through “zth”) of a list of incorrectly translated wordsand/or phrases.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results oftask 1_(—)5 to produce the fifth intermediate result (R1-5), which isthe list of incorrectly translated words and/or phrases. In particular,the processing module of DST execution 1 is engaged to aggregate thefirst through “zth” partial results of the list of incorrectlytranslated words and/or phrases to produce the fifth intermediateresult. The processing module stores the fifth intermediate result asnon-DS error encoded data in the scratchpad memory or in another sectionof memory of DST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the fifth intermediate result. To begin theencoding, the DST client module partitions the fifth intermediate result(R1-5) into a plurality of partitions (e.g., R1-5_(—)1 through R1-5_z).For each partition of the fifth intermediate result, the DST clientmodule uses the DS error encoding parameters of the data (e.g., DSparameters of data 2, which includes ⅗ decode threshold/pillar widthratio) to produce slice groupings. The slice groupings are stored in theintermediate result memory (e.g., allocated memory in the memories ofDST execution units 1-5 per the DST allocation information).

As is further shown in FIG. 36, the DSTN module is performing task1_(—)6 (e.g., translation errors due to non-words) on the list ofincorrectly translated words and/or phrases (e.g., the fifthintermediate result R1-5) and the list of non-words (e.g., the firstintermediate result R1-1). To begin, the DSTN module accesses the listsand partitions them into a corresponding number of partitions.

For each pair of partitions (e.g., partition R1-1_(—)1 and partitionR1-5_(—)1), the DSTN identifies a set of its DT execution modules 90 toperform task 1_(—)6 in accordance with the DST allocation information(e.g., DT execution modules 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1).For each pair of partitions, the allocated set of DT execution modulesexecutes task 1_(—)6 to produce partial results 102 (e.g., 1^(st)through “zth”) of a list of incorrectly translated words and/or phrasesdue to non-words.

As indicated in the DST allocation information of FIG. 32, DST executionunit 2 is assigned to process the first through “zth” partial results oftask 1_(—)6 to produce the sixth intermediate result (R1-6), which isthe list of incorrectly translated words and/or phrases due tonon-words. In particular, the processing module of DST execution 2 isengaged to aggregate the first through “zth” partial results of the listof incorrectly translated words and/or phrases due to non-words toproduce the sixth intermediate result. The processing module stores thesixth intermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 2.

DST execution unit 2 engages its DST client module to slice groupingbased DS error encode the sixth intermediate result. To begin theencoding, the DST client module partitions the sixth intermediate result(R1-6) into a plurality of partitions (e.g., R1-6_(—)1 through R1-6_z).For each partition of the sixth intermediate result, the DST clientmodule uses the DS error encoding parameters of the data (e.g., DSparameters of data 2, which includes ⅗ decode threshold/pillar widthratio) to produce slice groupings. The slice groupings are stored in theintermediate result memory (e.g., allocated memory in the memories ofDST execution units 2-6 per the DST allocation information).

As is still further shown in FIG. 36, the DSTN module is performing task1_(—)7 (e.g., correctly translated words and/or phrases) on the list ofincorrectly translated words and/or phrases (e.g., the fifthintermediate result R1-5) and the list of unique words (e.g., the secondintermediate result R1-2). To begin, the DSTN module accesses the listsand partitions them into a corresponding number of partitions.

For each pair of partitions (e.g., partition R1-2_(—)1 and partitionR1-5_(—)1), the DSTN identifies a set of its DT execution modules 90 toperform task 1_(—)7 in accordance with the DST allocation information(e.g., DT execution modules 1_(—)2, 2_(—)2, 3_(—)2, 4_(—)2, and 5_(—)2).For each pair of partitions, the allocated set of DT execution modulesexecutes task 1_(—)7 to produce partial results 102 (e.g., 1^(st)through “zth”) of a list of correctly translated words and/or phrases.

As indicated in the DST allocation information of FIG. 32, DST executionunit 3 is assigned to process the first through “zth” partial results oftask 1_(—)7 to produce the seventh intermediate result (R1-7), which isthe list of correctly translated words and/or phrases. In particular,the processing module of DST execution 3 is engaged to aggregate thefirst through “zth” partial results of the list of correctly translatedwords and/or phrases to produce the seventh intermediate result. Theprocessing module stores the seventh intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 3.

DST execution unit 3 engages its DST client module to slice groupingbased DS error encode the seventh intermediate result. To begin theencoding, the DST client module partitions the seventh intermediateresult (R1-7) into a plurality of partitions (e.g., R1-7_(—)1 throughR1-7_z). For each partition of the seventh intermediate result, the DSTclient module uses the DS error encoding parameters of the data (e.g.,DS parameters of data 2, which includes ⅗ decode threshold/pillar widthratio) to produce slice groupings. The slice groupings are stored in theintermediate result memory (e.g., allocated memory in the memories ofDST execution units 3-7 per the DST allocation information).

In FIG. 37, the distributed storage and task network (DSTN) module isperforming task 2 (e.g., find specific words and/or phrases) on the data92. To begin, the DSTN module accesses the data and partitions it into aplurality of partitions 1-z in accordance with the DST allocationinformation or it may use the data partitions of task 1_(—)1 if thepartitioning is the same. For each data partition, the DSTN identifies aset of its DT execution modules 90 to perform task 2 in accordance withthe DST allocation information. From data partition to data partition,the set of DT execution modules may be the same, different, or acombination thereof. For the data partitions, the allocated set of DTexecution modules executes task 2 to produce partial results 102 (e.g.,1^(st) through “zth”) of specific words and/or phrases found in the datapartitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 7 is assigned to process the first through “zth” partial results oftask 2 to produce task 2 intermediate result (R2), which is a list ofspecific words and/or phrases found in the data. The processing moduleof DST execution 7 is engaged to aggregate the first through “zth”partial results of specific words and/or phrases to produce the task 2intermediate result. The processing module stores the task 2intermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 7.

DST execution unit 7 engages its DST client module to slice groupingbased DS error encode the task 2 intermediate result. To begin theencoding, the DST client module determines whether the list of specificwords and/or phrases is of a sufficient size to partition (e.g., greaterthan a Terra-Byte). If yes, it partitions the task 2 intermediate result(R2) into a plurality of partitions (e.g., R2_(—)1 through R2_m). If thetask 2 intermediate result is not of sufficient size to partition, it isnot partitioned.

For each partition of the task 2 intermediate result, or for the task 2intermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes ⅗decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-4, and 7).

In FIG. 38, the distributed storage and task network (DSTN) module isperforming task 3 (e.g., find specific translated words and/or phrases)on the translated data (R1-3). To begin, the DSTN module accesses thetranslated data (from the scratchpad memory or from the intermediateresult memory and decodes it) and partitions it into a plurality ofpartitions in accordance with the DST allocation information. For eachpartition, the DSTN identifies a set of its DT execution modules toperform task 3 in accordance with the DST allocation information. Frompartition to partition, the set of DT execution modules may be the same,different, or a combination thereof. For the partitions, the allocatedset of DT execution modules 90 executes task 3 to produce partialresults 102 (e.g., 1^(st) through “zth”) of specific translated wordsand/or phrases found in the data partitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 5 is assigned to process the first through “zth” partial results oftask 3 to produce task 3 intermediate result (R3), which is a list ofspecific translated words and/or phrases found in the translated data.In particular, the processing module of DST execution 5 is engaged toaggregate the first through “zth” partial results of specific translatedwords and/or phrases to produce the task 3 intermediate result. Theprocessing module stores the task 3 intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 7.

DST execution unit 5 engages its DST client module to slice groupingbased DS error encode the task 3 intermediate result. To begin theencoding, the DST client module determines whether the list of specifictranslated words and/or phrases is of a sufficient size to partition(e.g., greater than a Terra-Byte). If yes, it partitions the task 3intermediate result (R3) into a plurality of partitions (e.g., R3_(—)1through R3_m). If the task 3 intermediate result is not of sufficientsize to partition, it is not partitioned.

For each partition of the task 3 intermediate result, or for the task 3intermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes ⅗decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-4, 5, and 7).

FIG. 39 is a diagram of an example of combining result information intofinal results 104 for the example of FIG. 30. In this example, theresult information includes the list of specific words and/or phrasesfound in the data (task 2 intermediate result), the list of specifictranslated words and/or phrases found in the data (task 3 intermediateresult), the list of non-words found in the data (task 1 firstintermediate result R1-1), the list of unique words found in the data(task 1 second intermediate result R1-2), the list of translation errorsdue to non-words (task 1 sixth intermediate result R1-6), and the listof correctly translated words and/or phrases (task 1 seventhintermediate result R1-7). The task distribution module provides theresult information to the requesting DST client module as the results104.

FIG. 40A is a schematic block diagram of another embodiment of adistributed computing system that includes a computing device 350, adistributed storage and task (DST) unit 352, a plurality of alternateDST units 354, and a plurality of other alternate DST units 356. EachDST unit 352, 354, and 356 may be implemented by one or more of astorage server, a distributed computing server, a memory module, amemory device, a user device, a DST processing unit, a dispersed storage(DS) unit, and a DS processing unit. The computing device 350 may beimplemented utilizing one or more of a DST processing unit, a DSTexecution unit, a DST unit 352, a DS unit, a storage server, adistributed computing server, a user device, a DS processing unit, analternate DST unit 354, and another alternate DST unit 356.

The system functions to execute distributed computing tasks. Thecomputing device 350 outputs slices 96 and partial tasks 98 forexecution on the slices 96 to the DST unit 352. The DST unit 352executes the partial task 98 on a slice 96 to produce an intermediatepartial result. The DST unit 352 determines to suspend partial taskexecution when a performance factor of the DST unit is unfavorable. Forexample, the DST unit 352 determines to suspend partial task executionwhen execution of the dispersed storage activities compares unfavorablyto a dispersed storage performance threshold level (e.g., read sliceresponses are too slow).

The DST unit 352 issues one or more continuation requests 358 to one ormore alternate DST units 354. Each continuation request 358 includes oneor more of a partial task execution state, a sub-partial task, and theintermediate partial result. An alternate DST unit 354 of the pluralityof alternate DST units receives a corresponding continuation request 358and executes the sub-partial task on a slice and/or the intermediatepartial result to produce partial results 102. The alternate DST unit354 outputs the partial results 102 to the computing device 350.Alternatively, or in addition to, the alternate DST unit 354 mayfunction in a similar manner to the DST unit 352 to further determine tosuspend partial task processing by the alternate DST unit 354 and issueanother continuation request 358 to another alternate DST unit 356 ofthe plurality of other alternate DST units.

FIG. 40B is a flowchart illustrating an example of executing distributedcomputing tasks. The method begins at step 360 where a processing module(e.g., of a distributed storage and task (DST) unit) receives a slicegrouping and a partial task. The method continues at step 362 where theprocessing module initiates execution of the partial task on the slicegrouping to produce intermediate partial results. The method continuesat step 364 where the processing module determines to suspend partialtask execution. The determining may be based on one or more of a memoryutilization level, a task processing resource utilization level, adispersed storage performance level, a distributed computing performancelevel, and a pending task execution queue level. The method continues atstep 366 where the processing module generates at least one continuationrequest based on one or more of the intermediate partial results, theslice grouping, and the partial task. The generating includesidentifying how many continuation requests to generate based on one ormore of a desired partial task execution time frame, task processingcapability levels of one or more alternate DST units, the intermediatepartial results, the slice grouping, and the partial task.

The method continues at step 368 where the processing module selects atleast one alternate DST unit. The selecting includes selecting a numberof DST units to substantially match the number of continuation requestand identifying the at least one alternate DST unit based on one or moreof a DST unit memory availability level and a DST unit processingresource availability level. The method continues at step 370 where theprocessing module outputs the at least one continuation request to theat least one alternate DST unit.

FIG. 41A is a schematic block diagram of another embodiment of adistributed computing system that includes a plurality of processingmodules 372 and a dispersed storage (DS) unit set 374. The DS unit set374 includes a set of DS units 376. Each DS unit 376 may be implementedby one or more of a distributed storage and task (DST) unit, a DSTexecution unit, a storage server, a distributed computing server, amemory module, a memory device, a user device, a DST processing unit, adispersed storage (DS) unit, and a DS processing unit. The plurality ofprocessing modules 372 may be associated with one or more computingdevices. For example, each processing module 372 is affiliated with adifferent distributed task (DT) module of a plurality of DST executionunits.

The system functions to execute tasks. The plurality of processingmodules 372 provides task execution capacity to execute a plurality ofpending tasks. The DS unit set 374 provides storage for one or moredispersed queues stored as plurality of sets of encoded queue slices.Each queue of the one or more dispersed queues includes one or morequeue entries where each queue entry includes one or more tasks (e.g.,distributed computing tasks). A first queue of the one or more dispersedqueues includes an unassigned queue to hold queue entries that have notbeen assigned to a processing module for task execution of one or moretasks associated with each queue entry of the queue entries. Otherqueues of the one or more dispersed queues may be utilized to storequeue entries associated with assigned tasks.

A processing module 372 associated with available task executioncapacity obtains a queue entry from the unassigned queue by reading it(e.g., issuing queue entry requests 378 and receiving queue entryresponses 380 that includes slices of the queue entry) and immediatelyissues delete requests to the DS unit set 374 for slices associated withthe queue entry (e.g., issues queue entry request 378 that includesdelete slice requests). The queue entry requests 378 include one or moreof a list request, a delete request, a write request, a read request, acommit transaction request, a finalize transaction requests, and arollback transaction request. The processing module 372 stores the queueentry in an assigned queue of the DS unit set (e.g., processing moduleissues write requests, commit request, and finalize requests of athree-phase commit process). Next, the processing module 372 issuesdelete requests for the slices of the queue entry in the assigned queueto provide a lock on the queue entry (e.g., but does not send committransaction requests for the delete requests yet). The processing module372 initiates execution of one or more tasks of the queue entry. Uponcompletion of the one or more tasks of the queue entry, the processingmodule 372 issues the commit transaction requests for the deleterequests for the slices of the queue entry in the assigned queue tocomplete deletion of the queue entry from the assigned queue.Alternatively, upon a failure, the processing module 372 issues arollback transaction for the delete requests for the assigned queue toremove the lock without the leading the queue entry.

Another processing module 372 of the plurality of processing modules mayread the queue entry from the assigned queue and issue delete requestsfor the slices of the queue entry to determine whether a lock is presenton the queue entry. The other processing module 372 determines that thelock is present when receiving a queue entry response that includes awrite conflict error in response to the delete requests. When the queueentry response 380 does not indicate the conflict error (e.g., no lockactive), the other processing module 372 stores the queue entry in theunassigned queue (e.g., issuing queue entry requests to write slices ofthe queue entry to the unassigned queue). Next, the other processingmodule 372 issues a commit transaction request for the delete requestsfor the queue entry of the assigned queue to complete deletion of thequeue entry from the assigned queue. Alternatively, or in addition to,the other processing module 372 may execute tasks of the queue entry aspreviously described. When the queue entry response includes a deleteresponse that indicates a conflict or lock error, the other processingmodule 372 may attempt to identify another queue entry of the assignedqueue that is not locked.

FIG. 41B is a flowchart illustrating an example of executing tasks. Themethod begins at step 382 where a processing module (e.g., of acomputing device) obtains a queue entry from an unassigned task queuestored in a dispersed storage network (DSN) memory. The obtainingincludes one or more of determining that available task executioncapacity exists, outputting list requests, interpreting list responsesto identify the queue entry, and retrieving the queue entry by issuingread requests for slices of the queue entry (e.g., receiving readresponses including the slices of the queue entry and decoding theslices using a dispersed storage error coding function to produce thequeue entry).

The method continues at step 384 where the processing module initiatesdeletion of the queue entry from the unassigned task queue. Theinitiating includes issuing delete slice requests to the DSN memory forthe slices of the queue entry (e.g., but no commit transaction requestsyet). The method continues at step 386 where the processing modulestores the queue entry in an assigned task queue. The storing includesone or more of identifying the assigned task queue, generating writeslice requests for the slices of the queue entry, outputting the writeslice requests to the DSN memory, issuing commit transaction requests tothe DSN memory, and issuing finalize transaction requests to the DSNmemory to complete a three-phase dispersed storage process.

The method continues at step 388 where the processing module completesdeletion of the queue entry from the unassigned task queue. Thecompletion of the deletion includes issuing commit transaction requestsand finalize transaction requests to the DSN memory for a transactionassociated with the initiation of the deletion of the queue entry. Themethod continues at step 390 where the processing module initiatesdeletion of the queue entry in the assigned task queue. The initiationof the deletion includes issuing delete slice requests for the slices ofthe queue entry to the DSN memory.

The method continues at step 392 where the processing module initiatesexecution of one or more tasks associated with the queue entry. Themethod continues at step 394 where the processing module determineswhether the execution of the one or more tasks is successful (e.g.,completed with available resources). The method branches to step 398when the execution of the one or more tasks is not successful. Themethod continues to step 396 when the execution of the one or more tasksis successful. The method continues at step 396 where the processingmodule completes deletion of the queue entry in the assigned task you.The completing of the deletion includes outputting commit transactionrequests associated with the delete slice requests.

The method continues at step 398 where the processing module issues arollback transaction for the initiated deletion of the queue entry inthe assigned task queue when the execution of the one or more tasks isnot successful. The method continues at 400 where an alternateprocessing module obtains the queue entry from the assigned task queue(e.g., in a similar fashion as the processing module obtains the queueentry from the unassigned task queue). The method continues at step 402where the alternate processing module determines whether the queue entryis locked. The determining includes issuing a delete slice request for aslice of the queue entry, receiving a delete slice response, andindicating that the queue entry is locked when receiving a locked errormessage. When not locked, the method continues at step 404 where thealternate processing module stores the queue entry in the unassignedqueue. Alternatively, the alternate processing module initiatesexecution of the one or more tasks associated with the queue entry. Themethod continues at step 406 where the alternate processing modulecompletes deletion of the queue entry in the assigned task queue. Thecompleting deletion includes issuing commit transaction requests andfinalize transaction requests to the DSN memory with regards to theissuing of the delete slice requests to determine whether the queueentry is locked.

FIG. 42A is a schematic block diagram of another embodiment of adistributed computing system that includes a computing device 410, atoken issuing entity 412, a distributed storage and task (DST) unit 414and a dispersed storage network (DSN) memory 416. The DSN memory 416includes at least one set of dispersed storage (DS) units 376. Each DSunit 376 may be implemented by one or more of a distributed storage andtask (DST) unit, a DST execution unit, a storage server, a distributedcomputing server, a memory module, a memory device, a user device, a DSTprocessing unit, a dispersed storage (DS) unit, and a DS processingunit. The computing device 410 and the token issuing entity 412 each maybe implemented as one or more of a DST unit 414, a DST processing unit,a DST execution unit, a DS unit 376 of the DSN memory 416, a storageserver, a user device and a distributed computing server.

The system functions to validate access by the computing device 410 tothe DSN memory 416 via the DST unit 414. The computing device 410authenticates with the token issuing entity 412 by issuing a tokenrequest 418, that includes credentials of the computing device, to thetoken issuing entity 412. The computing device 410 issues accessrestrictions in another token request 418 and/or the token request 418to the token issuing entity 412. The token request 418 includes one ormore of credentials of an existing authorized user of the DSN memory 416for which a distributed computing task will be executed and accessrestrictions including one or more of a time frame, a set of data to beaccessed, and identity of authorized requesting entities to access thedata, a write restriction, a read restriction, a delete restriction, alisting restriction, and other similar restrictions.

The token issuing entity 412 authenticates the computing device 410 whenreceiving credentials of the computing device. When authenticated, thetoken issuing entity 412 generates an access token 422 and issues atoken response 420 to the computing device 410 that includes the accesstoken 422. The token response 420 includes one or more of anauthentication indication and the access token 422 which includes one ormore of the access restrictions, the identity of the requesting entity,a signature generated using a private key of the token issuing entity,and a public key or digital certificate of the token issuing entity.

The computing device 410 receives the token response for 420 from thetoken issuing entity 412 and issues partial tasks 98 and the accesstoken 422 to the DST unit 414. The DST unit 414 identifies a DSN addressfor data required for a partial task of the partial task 98. The DSTunit 414 issues a data access request 424 using the DSN address to theDSN memory where the data access request 424 includes the access token422. A DS unit 376 of the DSN memory 416 receives the data accessrequest 424 and verifies the data access request 424 using the accesstoken 422. The DS unit 376 generates a data access response 426 based onthe verification and outputs the data access response 426 to the DSTunit 414. The verifying of the data access request 424 using the accesstoken 422 includes verifying that the data access request 424 would beauthorized when the same entity whose credentials were used to requestthe access token 422 had directly made the request, that the accessrequest does not violate any restrictions present an access token, andthat the signature is valid for the access token 422 and the certificateis that of a trusted token issuing entity (e.g., the token issuingentity 412).

The DST unit 414 receives the data access response 426 from the DS unit376 and recovers data from at least a decode threshold number of dataaccess responses 426 from the DSN memory 416 (e.g., decodes a decodethreshold number of slices using a dispersed storage error codingfunction to produce recovered data). Next, the DST unit 414 executes thepartial task on the recovered data to produce partial results 102. TheDST unit 414 outputs the partial results 102 to the computing device410.

FIG. 42B is a flowchart illustrating an example of validating access.The method begins at step 430 where a processing module (e.g., of acomputing device) authenticates with a token issuing entity. Theauthentication includes issuing credentials to the token issuing entity.The method continues at step 432 where the processing module of thecomputing device issues access restrictions to the token issuing entity.The issuing includes generating and outputting a token request to thetoken issuing entity. When authenticated, the method continues at step434 where the token issuing entity issues an access token to thecomputing device. The issuing includes generating and outputting asigned token response using a private key of the token issuing entity.

The method continues at step 436 where the processing module of thecomputing device issues the access token and a partial task to adistributed storage and task (DST) unit. Alternatively, or in additionto, the processing module of the computing device may authenticate withthe DST unit prior to issuing. The method continues at step 438 wherethe DST unit identifies a dispersed storage network (DSN) addressassociated with the partial task. The identifying includes at least oneof identifying required data for the partial task and accessing an index(e.g., a dispersed hierarchical index) based on a date identifier toobtain the DSN address. The method continues at step 440 where the DSTunit issues a data access request to the DSN using the DSN address wherethe request includes the access token.

The method continues at step 442 where a dispersed storage (DS) unit ofthe DSN authenticates the data access request. The authenticatingincludes one or more of verifying that the user of the access token isauthenticated to perform the requested DSN access, verify that no accessrestrictions included in the access token are violated, verify that thesignature of the access token is valid, and verify that the access tokencertificate was issued by a trusted token issuing entity. Whenauthenticated, the method continues at step 444 where the DS unit issuesa data access response to the DST unit based on the data access request.The issuing includes generating and outputting the data access responseto include a slice for a read request and an acknowledgment whenreceiving a write request.

The method continues at step 446 where the DST unit recovers data fromat least a decode threshold number of data access responses. Therecovering includes decoding the decode threshold number of slices usinga dispersed storage error coding function to produce the recovered data.The method continues at step 448 where the DST unit executes the partialtask on the recover data to produce a partial result.

FIG. 43A is a schematic block diagram of another embodiment of adistributed computing system that includes a computing device 450, aplurality of dispersed storage (DS) processing units 454, and thedispersed storage network (DSN) memory 416 of FIG. 42A. The computingdevice 450 and each DS processing unit 450 may be implemented as one ormore of a distributed storage and task (DST) unit, a DST processingunit, a DST execution unit, a DS unit 376 of the DSN memory 416, astorage server, a user device and a distributed computing server.

The system functions to provide access to data stored in the DSN memory416 as a plurality of blocks of data where each block is stored as oneor more sets of encoded data slices. The computing device 450 issues adata object request 456 to a first DS processing unit 454 of theplurality of DS processing units where the data object request 456includes a parallel operation indicator (e.g., utilize a bit torrentprotocol). The first DS processing unit 454 issues data accessinformation 458 (e.g., a torrent file) to the computing device 450 inresponse to receiving the data object request 456 where the data accessinformation 458 includes identities of other DS processing units 454(e.g., seeders) to utilize and retrieval of the data object and datablock mapping information. The data block mapping information includesone or more of a data object size, a block size, a number of blocks, asegment size, a number of segments per block, the data block rangesbased on affiliation of DS processing units 454 and data blocks, etc.For example, block size to be chosen as a multiple of segment size forimproved efficiency.

The computing device 450 generates one or more data block requests 460based on the data access information 458 from the first DS processingunit 454. The computing device 450 outputs the one or more data blockrequests 460 to a corresponding one or more other DS processing units454 in accordance with the data access information 458. Each other DSprocessing unit 454 of the one or more other DS processing units issuesslice access requests 464 to the DSN memory 416 in response to receivinga data block request 460 of the one or more data block requests. Theissuing includes mapping a range of requested data blocks to DSNaddresses utilized in generation of read slice access requests. Next,the DS processing unit 454 issues a data block response 462 to thecomputing device 450 based on slice access responses 466 received fromthe DSN memory 416. The issuing includes decoding at least a decodethreshold number of slices from the slice access responses 466 toreproduce one or more data segments of one or more corresponding datablocks. The computing device 450 regenerates the data object using datablocks from one or more receive data block responses 462 from the one ormore other DS processing units 454.

FIG. 43B is a flowchart illustrating an example of accessing data. Themethod begins at step 468 where a processing module (e.g., of acomputing device) issues a data object request to a dispersed storage(DS) processing unit. The request may include a parallel operationindicator. The method continues at step 470 where the DS processing unitissues data access information to the computing device in response toreceiving the data object request. The issuing includes at least one ofperforming an index lookup, performing a table lookup, and initiating aquery. Alternatively, the processing module obtains the data accessinformation from another source including at least one of a systemmanager, a user device, a registry lookup, a result of initiating aquery, and receiving the data access information. The method continuesat step 472 where the processing module of the computing devicegenerates one or more data block requests based on the data accessinformation. The generating includes identifying block ranges of thedata object and mapping the block ranges to the requests in accordancewith the data access information.

The method continues at step 474 where the processing module outputs theone or more data block requests to a corresponding one or more other DSprocessing units in accordance with the data access information. Theoutputting includes identifying the one or more other DS processingunits from the data axis information. The other DS processing units mayinclude the DS processing unit. The method continues at step 476 whereeach DS processing unit of the other DS processing units issues sliceaccess requests to a dispersed storage network (DSN) memory in responseto receiving a corresponding data block request. The issuing includesidentifying data segments corresponding to data blocks of the data blockrequest and generating the slice access requests using the segmentidentification.

The method continues at step 478 where each DS processing unit of theother DS processing units issues a data block response to the computingdevice based on receiving slice access responses from the DSN memory.The issuing includes receiving slices via the slice access responses,decoding the slices using a dispersed storage error coding function toproduce segments, and arranging the segments to produce data blocks inaccordance with the data access information. The method continues atstep 480 where the processing module of the computing device regeneratesa regenerated data object using one or more data block responses fromthe one or more other DS processing units. The regenerating includesaggregating data blocks of the data block responses in accordance withdata block mapping of the data access information (e.g., ordering).

FIGS. 44A, B, D, E, F are schematic block diagrams of an embodiment of adispersed storage network (DSN) illustrating example steps of modifyinga DSN memory data access response plan. The DSN includes a DSN memory,the network 24 of FIG. 1, and a computing device 492. The computingdevice 492 includes the distributed storage and task (DST) client module34 of FIG. 1. The DSN memory may include a DST execution unit pool 490that includes a pool of storage nodes. Each storage node may beimplemented with the DST execution unit 36 of FIG. 1. Each DST executionunit includes the processing module 84 of FIG. 3, the network interface169 of FIG. 11, and a computer readable storage medium. The computerreadable storage medium may be implemented with the memory 88 of FIG. 3.The memory 88 includes storage sections for one or more of operationalinstructions and slice portions. One or more of the processing modules84 executes the operational instructions.

The DST execution unit pool 490 stores a multitude of encoded datafiles. Each encoded data file includes data partitions where each datapartition includes one portion of at least a portion of the one encodeddata file of the multitude of encoded data files. Each data partitionincludes one or more data segments where each data segment is dispersedstorage error encoded in accordance with dispersed storage errorencoding parameters to produce a set of encoded data slices. Thedispersed storage error encoding parameters includes one or more of awidth number, a write threshold number, a read threshold number, and adecode threshold number. The DST execution unit pool 490 includes atleast a width number of DST execution units for each set of dispersedstorage error encoding parameters. As a specific example, the DSTexecution unit pool 490 includes five DST execution units 1-5 when amaximum width number of corresponding sets of dispersed storage errorencoding parameters is four.

As a specific example, the DST execution unit pool 490 stores encodeddata file A and encoded data file B. For instance, data file A includesan electronic book with 10 chapters (e.g., 10 portions) where a firstchapter includes three subchapters (e.g., 3 partitions). Each subchapter(e.g., partition) includes corresponding one or more data segments. Eachdata segment is encoded in accordance with a first set of dispersedstorage error encoding parameters to produce a corresponding set ofencoded data slices that includes four encoded data slices when thewidth number of the first set of dispersed storage error encodingparameters is four. For example, the corresponding one or more datasegments of subchapter 1 of the first chapter (e.g., first partition)are encoded to produce four groups of partition slices A-1-1, A-2-1,A-3-1, and A-4-1. As such, a first group of partition slices A-1-1includes first pillar slices of the first partition of the data file A.As another example, the corresponding one or more data segments ofsubchapter 2 of the first chapter (e.g., second partition) are encodedto produce another four groups of partition slices A-1-2, A-2-2, A-3-2,and A-4-2. As such, a third group of partition slices A-3-2 includesthird pillar slices of the second partition of the data file A.

As another instance of the DST execution unit pool 490 storing theencoded data files A and B, data file B includes a movie with 5 chapters(e.g., 5 portions) where a first movie chapter includes two moviesubchapters (e.g., 2 partitions). Each movie subchapter (e.g.,partition) includes corresponding one or more data segments. Each datasegment is encoded in accordance with a second set of dispersed storageerror encoding parameters to produce a corresponding set of encoded dataslices that includes three encoded data slices when the width number ofthe second set of dispersed storage error encoding parameters is three.For example, the corresponding one or more data segments of moviesubchapter 1 of the first movie chapter (e.g., first movie partition)are encoded to produce three groups of partition slices B-1-1, B-2-1,and B-3-1.

FIG. 44A illustrates accessing the DSN memory. As a specific example,the computing device 492 determines to recover the first chapter of theelectronic book with 10 chapters. The determining includes at least oneof receiving a request to recover the electronic book, a random chapterselection, and a specific chapter selection. The computing device 492identifies the three partitions corresponding to the three subchaptersof the first chapter. The identifying may be based on one or more ofinitiating a query, performing a lookup, receiving a response, andcalculating subchapter identifiers based on an index of the electronicbook.

With the three partitions identified, the DST client module 34identifies DST execution units of the DST execution unit pool 490associated with storing the three partitions of the first chapter of thedata file A (e.g., the electronic book). The computing device 492 maymaintain a slice location table 494, where the slice location table 494includes a plurality of entries corresponding to the multitude ofencoded data files stored by the DST execution unit pool 490. Each entryincludes a partition entry of a partition field 496 and unit identifier(ID) a DST execution unit ID field 498. As a specific example, a firstentry indicates that all partitions of data file A are stored in the DSTexecution units 1-4 and a second entry indicates that all partitions ofdata file B are stored in the DST execution units 1-3.

Having identified the DST execution units associated with storing thethree partitions of the first chapter of the data file A, the DST clientmodule 34 issues slice access requests 500 to the identified DSTexecution units 1-4 of the DST execution unit pool 490, where the sliceaccess requests 500 corresponds to the three partitions of the sets ofencoded data slices. As a specific example, the DST client module 34generates and sends slice access requests A-1-x to the DST executionunit 1, slice access requests A-2-x to the DST execution unit 2, sliceaccess requests A-3-x to the DST execution unit 3, and slice accessrequests A-4-x to the DST execution unit 4. Each slice access requestincludes at least one of a read slice requests, a write slice request, adelete slice request, and a list slice request. For instance, the sliceaccess requests A-1-x includes a first read slice request for the groupof partition slices A-1-1 associated with pillar 1 encoded data slicesof the first subchapter, a second read slice request for the group ofpartition slices A-1-2 associated with pillar 1 encoded data slices ofthe second subchapter, and a third read slice request for the group ofpartition slices A-1-3 associated with pillar 1 encoded data slices ofthe third subchapter.

Having issued the slice access request 500, the DST client module 34receives slice access responses 502, where the slice access responses502 includes the three partitions of the sets of encoded data slices. Asa specific example, the slice access responses 502 includes slice accessresponses A-1-x, A-2-x, A-3-x, and A-4-x. Each slice access responseincludes at least one of a read slice response, a write slice response,a delete slice response, and a list slice response. For instance, theslice access responses A-1-x includes a first read slice response forthe group of partition slices A-1-1 associated with the pillar 1 encodeddata slices of the first subchapter, a second read slice response forthe group of partition slices A-1-2 associated with pillar 1 encodeddata slices of the second subchapter, and a third read slice responsefor the group of partition slices A-1-3 associated with pillar 1 encodeddata slices of the third subchapter. Having received the slice accessresponses 502, the DST client module 34 dispersed storage error decodeseach set of encoded data slices of the three partitions of sets ofencoded data slices using the first set of dispersed storage errorencoding parameters to reproduce subchapters 1-3 (e.g., partitions 1-3)of the first chapter.

FIG. 44B illustrates initial steps of the example of modifying the DSNmemory data access response plan. As a specific example, the one or moreof the processing modules 84 executes operational instructions from afirst storage section of the computer readable storage medium (e.g., acorresponding memory 88) that causes the one or more of the processingmodules 84 to obtain data access response performance data 504 for eachof the DST execution units 1-5 (e.g., storage nodes) in the DSTexecution unit pool 490 (e.g., pool of storage nodes). The obtainingincludes at least one of issuing one or more requests for the dataaccess response performance data 504, receiving at least one responsethat includes the data access response performance data 504, andreceiving an unsolicited message that includes the data access responseperformance data 504. For instance, each DST execution unit 1-5generates data access response performance data 504 corresponding to theDST execution unit and sends its data access response performance data504 to each other DST execution unit 1-5. The data access responseperformance data 504 includes one or more of a throughput level, a dataresponse latency level, a memory availability level, and a processingresource availability level.

Having obtained the data access response performance data 504 for eachof the DST execution units 1-5, the one or more of the processingmodules 84 analyzes the data access response performance data 504 forthe DST execution unit pool 490 to modify a data access response plan508 to produce a modified data access response plan 510. The data accessresponse plan 508 includes, for at least a portion of one of themultitude of encoded data files, a per data segment encoded data sliceresponse level (e.g., how to recover each data segment), identity of aset of DST execution units (e.g., a set of storage nodes of the pool ofstorage nodes) storing encoded data slices of the at least a portion ofthe one of the multitude of encoded data files (e.g., initially DSTexecution units 1-4 for the data file A and DST execution units 1-3 fordata file B), and identity of preferred DST execution units (e.g.,preferred storage nodes) of the set of DST execution units (e.g.,storage nodes) to respond to a data access request for the at least aportion of the one of the multitude of encoded data files. The modifyingof the data access response plan 508 to produce the modified data accessresponse plan 510 is discussed in an example in greater detail withreference to FIG. 44C.

FIG. 44C is a diagram illustrating an example of a storage node poolassignment table 506 utilized when modifying the data access responseplan 508 to produce the modified data access response plan 510. Thestorage node pool assignment table 506 includes table entries for eachDST execution unit of the DST execution unit pool 490. Each table entryincludes a unit identifier of a DST execution unit ID field 498, anentry of a field of the data access response plan 508, a data accessresponse performance data entry of a data access response performancedata field 504, and a modified data access response plan entry of afield of the modified data access response plan 510. Each field of thedata access response plan 508 and the modified data access response plan510 includes respond entries of a respond field 512 and don't respondentries of a don't respond field 514.

The respond entries correspond to identifiers of which groups of encodeddata slices are to be included in a slice access response directedtowards the preferred storage nodes. For example, a first entry of thestorage node pool assignment table 506 indicates that DST execution unit1, in accordance with the data access response plan 508, shall respondas the preferred storage node to slice access requests to produce sliceaccess responses A-1-x for partition slices A-1-1, A-1-2, and A-1-3 andshall respond to slice access requests to produce slice access responsesB-1-x for partition slices B-1-1 and B-1-2. Other respond entries of thedata access response plan 508 indicates that DST execution units 2-4 arealso preferred storage nodes in accordance with the data access responseplan 508 with regards to other partition slices (e.g., unit 2 preferredfor A-2-x, unit three preferred for A-3-x, and unit 4 preferred forA-4-x).

The don't respond entries correspond to identifiers of which groups ofencoded data slices are not to be included in another slice accessresponse. For example, the first entry of the storage node poolassignment table 506 indicates that DST execution unit 1, in accordancewith the data access response plan 508, has no encoded data slices toexclude from the other slice access response.

The data access response plan 508 is modified to include an indicationthat one of the preferred storage nodes has an undesired performancelevel and to include an alternative data access response for the one ofthe preferred storage nodes having the undesired performance level. Thealternative data access response includes at least one of discardingselected slice access requests; forwarding of the selected slice accessrequests from a source DST execution unit to destination DST executionunit; sending one or more of the data access response plan 508, the dataaccess response performance data 504, and the modified data accessresponse plan 510 to one or more requesting entities; facilitatingstorage of a copy of encoded data slices of the at least a portion ofthe one of the multitude of encoded data files in one or more other DSTexecution units; and issuing slice access responses corresponding to theselected slice access requests.

As a specific example of including the indication that the one of thepreferred storage nodes has the undesired performance level, theprocessing module 84 of DST execution unit 5 receives the data accessresponse performance data 504 and analyzes the data access responseperformance data 504 to determine that the DST execution units 1 and 2have the undesired performance level and that DST execution units 3-5have a desired performance level. For instance, the processing module 84indicates that the DST execution unit 1 has the undesired performancelevel when a data response latency level of the data access responseperformance data 504 from the DST execution unit 1 compares unfavorably(e.g., is greater than) to a data response latency threshold level.

As a specific example of including the alternative data access responsefor the one of the preferred storage nodes having the undesiredperformance level, the processing module 84 of the DST execution unit 5identifies the encoded data slices of the at least a portion of the oneof the multitude of encoded data files. Next, the processing module 84removes identity of the partition slices A-1-x from the respond field512 of DST execution unit 1. Next, the processing module 84 selectsanother DST execution unit based on an availability to perform thealternative data access response. For instance, the processing module 84selects the DST execution unit 5 that is associated with the desiredlevel of performance. Alternatively, the processing module 84 selects aset of other DST execution units based on the availability to performthe alternative data access response, where the set of other DSTexecution units includes the other DST execution unit. For instance, theprocessing module 84 selects DST execution units 5 and 4.

Having selected another DST execution unit, the processing module 84includes the identity of the partition slices A-1-x in the don't respondfield 514 of DST execution unit 1 and includes the identity of thepartition slices A-1-x in the respond field 512 of DST execution unit 5(e.g., desired level of performance) of the modified data accessresponse plan 510 when the DST execution unit 1 of the preferred DSTexecution units of the data access response plan 508 has the undesiredperformance level and the alternative data access response includeseither of the forwarding of selected slice access requests and thefacilitating storage of the copy of encoded data slices of the at leasta portion of the one of the multitude of encoded data files in the oneor more other DST execution units.

As another specific example of including the alternative data accessresponse for the one of the preferred storage nodes having the undesiredperformance level, the processing module 84 of the DST execution unit 5removes identity of the partition slices A-2-x and B-2-x from therespond field 512 of DST execution unit 2 and includes the identity ofthe partition slices A-2-x and B-2-x in the don't respond field 514 ofthe modified data access response plan 510 when the DST execution unit 2of the preferred DST execution units of the data access response plan508 has the undesired performance level and the alternative data accessresponse includes the discarding selected slice access requests.

FIG. 44D illustrates further steps of the example of modifying the DSNmemory data access response plan. As a specific example, with themodified data access response plan 510 produced, the one or more of theprocessing modules 84 executes operational instructions from the first,or other, storage section of the computer readable storage medium (e.g.,corresponding memory 88) that causes the one or more of the processingmodules 84 to distribute the modified data access response plan 510 tothe DST execution unit pool 490. For instance, the processing modules 84of DST EX unit 5 sends the modified data access response plan 510 toeach of DST EX units 1-4. As another instance, the processing modules 84of DST EX unit 5 sends the modified data access response plan 510 to DSTEX units 4, processing modules 84 of DST EX unit 4 sends the modifieddata access response plan 510 to DST EX units 3 etc.

Alternatively, or in addition to, the one or more of the processingmodules 84 distributes the modified data access response plan 510 to oneor more requesting entities. As a specific example, the processingmodules 84 of DST EX unit 5 sends, via the network interface 169 of DSTEX unit 5, the modified data access response plan 510 to the computingdevice 492 (e.g., the one or more requesting entities). As anotherspecific example, the processing modules 84 of DST EX unit 5 updates,via the network interface 169 of DST EX unit 5, a system registry (e.g.,part of the DSTN managing unit 18 of FIG. 1) to include the modifieddata access response plan 510. As yet another specific example, theprocessing modules 84 of DST EX unit 5 issues, via the network interface169 of DST EX unit 5, a slice access response 502 to the computingdevice 492 (e.g., one of the one or more requesting entities), where theslice access response 502 includes the modified data access responseplan 510, when receiving a slice access request 500 from the computingdevice 492.

When the one or more of the processing modules 84 distributes themodified data response plan 510 to the computing device 492, a DSTclient module 34 updates the slice location table 494 to include changesresulting from modification of the data response plan 508 to produce themodified data response plan 510. As a specific example, the DST clientmodule 34 updates the slice location table 494 to indicate thatpartition slices A-1-x shall be accessed from DST execution unit 5rather than DST execution unit 1 (e.g., undesired level of performance),partition slices A-2-x shall not be accessed even though they are stillstored by DST execution unit 2 1 (e.g., undesired level of performance),partition slices A-3-x shall continue to be accessed from DST executionunit 3, partition slices A-4-x shall continue to be access from DSTexecution unit 4, partition slices B-1-x shall continue to be accessedfrom DST execution unit 1, partition slices B-2-x shall not be accessedeven though they are still stored by DST execution unit 2, and partitionslices B-3-x shall continue to be accessed from DST execution unit 3.

When the alternative data access response includes the facilitatingstorage of the copy of encoded data slices of the at least a portion ofthe one of the multitude of encoded data files in one or more other DSTexecution units, having identified the encoded data slices of the atleast a portion of the one of the multitude of encoded data files andhaving selected the other DST execution unit, the one or more of theprocessing modules 84 executes operational instructions from the first,or other, storage section of the computer readable storage medium (e.g.,corresponding memory 88) that causes the one or more of the processingmodules 84 to facilitate the selected other DST execution unit storing acopy of at least some of the encoded data slices of the at least aportion of the one of the multitude of encoded data files. As a specificexample, DST execution unit 1 issues a replicate slice request forpartition slices A-1-x to DST execution unit 5, where the replicateslice request includes one or more of the partition slices A-1-x, atemporary storage indicator, and slice names corresponding to thepartition slices A-1-x. As another specific example, the DST executionunit 5 interprets the modified data access response plan 510 and issuesa read slice access request 500 to DST execution unit 1 to retrieve thepartition slices A-1-x. As yet another specific example, the DSTexecution unit 4 interprets the modified data access response plan 510,issues the read slice access request 500 to DST execution unit 1 toretrieve the partition slices A-1-x, and issues a write slice accessrequest 500 to DST execution unit 5.

Alternatively, when the processing module 84 selects the set of otherDST execution units based on the availability to perform the alternativedata access response, where the set of other DST execution unitsincludes the other DST execution unit, the one or more of the processingmodules 84 executes operational instructions from the first, or other,storage section of the computer readable storage medium (e.g.,corresponding memory 88) that causes the one or more of the processingmodules 84 to facilitate the selected set of other DST execution unitsstoring the copy of the at least some of the encoded data slices of theat least a portion of the one of the multitude of encoded data files. Asa specific example, DST execution unit 1 issues the replicate slicerequest for partition slices A-1-x to DST execution units 4 and 5 whenthe selected set of other DST execution units includes DST executionunits 4 and 5. As another specific example, each of DST execution units4 and 5 interprets the modified data access response plan 510 and issuescorresponding read slice access requests 500 to DST execution unit 1 toretrieve the partition slices A-1-x. As yet another specific example,the DST execution unit 4 interprets the modified data access responseplan 510, issues the read slice access request 500 to DST execution unit1 to retrieve the partition slices A-1-x for storage therein, and issuesthe write slice access request 500 to DST execution unit 5 for storagetherein.

Having facilitated the selected set of other DST execution unit storingthe copy of the at least some of the encoded data slices of the at leasta portion of the one of the multitude of encoded data files, the one ormore of the processing modules 84 selects one of the selected set ofother DST execution units to function as the other DST execution unitwith regards to responding to access requests directed to the one of thepreferred DST execution units. As a specific example, the processingmodules 84 of DST execution unit 5 selects DST execution unit 5 as theother DST execution unit when DST execution unit 5 has a best level ofresource availability of the DST execution unit pool 490.

FIG. 44E illustrates further steps of the example of modifying the DSNmemory data access response plan. As a specific example, the one or moreof the processing modules 84 executes operational instructions from asecond storage section of the computer readable storage medium (e.g., acorresponding memory 88) that causes the one or more of the processingmodules 84 to receive, via the network interfaces 169 of the preferredDST execution units 1-4, corresponding portions of a data access request(e.g., slice access requests 500) for the at least a portion of the oneof the multitude of encoded data files (e.g., partitions 1-3). Forexample, the DST client module 34 identifies the preferred DST executionunits 1-4 in accordance with the slice location table 494 when the DSTclient module 34 has not received the modified data access response plan510 and the at least a portion of the one of the multitude of encodeddata files includes the three subchapters (e.g., partitions 1-3) of thefirst chapter of the electronic book. Having identified the preferredDST execution units 1-4, the DST client module 34 issues slice accessrequests 500 that includes slice access requests A-1-x (e.g., for slicepartitions A-1-1, A-1-2, and A-1-3) issued to DST execution unit 1,slice access requests A-2-x issued to DST execution unit 2, slice accessrequests A-3-x issued to DST execution unit 3, and slice access requestsA-4-x issued to DST execution unit 4.

Having received the slice access request 500, the one or more of theprocessing modules 84 of the DST execution unit pool 490 accesses themodified data access response plan 510 (e.g., retrieve from memory 88,obtain from another DST execution unit) and processes one of thecorresponding portions of the data access request in accordance with thealternative data access response. As a specific example, the processingmodule 84 of the one of the preferred DST execution units (e.g., unit 1)having the undesired performance level or the processing module 84 ofthe other DST execution unit (e.g., unit 5) of the pool of DST executionunits 1-5, processes the one of the corresponding portions (e.g., sliceaccess requests A-1-x, slice access requests A-2-x, etc.) of the dataaccess request in accordance with the alternative data access response.For instance, the processing module 84 of DST execution unit 1 processesslice access requests A-1-x when the one of the corresponding portionsof the data access request is directed towards the one of the preferredDST execution units (e.g., units 1 or 2) having the undesiredperformance level. As another instance, the processing module 84 of DSTexecution unit 5 processes slice access requests A-1-x when the one ofthe corresponding portions of the data access request is directedtowards the one of the preferred DST execution units (e.g., unit 1)having the undesired performance level.

As a specific example of the processing module 84 of the one of thepreferred DST execution units having the undesired performance levelprocessing the one of the corresponding portions of the data accessrequest, the processing module 84 of DST execution unit 2 discards theone of the corresponding portions of the data access request (e.g.,slice access requests A-2-x) when the alternative data access responseincludes an indication that data access requests for the at least aportion of the one of the multitude of encoded data files are to bediscarded.

As another a specific example of the processing module 84 of the one ofthe preferred DST execution units having the undesired performance levelprocessing the one of the corresponding portions of the data accessrequest, the processing module 84 of DST execution unit 1 forwards, viathe network interface 169 of DST execution unit 1, the one of thecorresponding portions of the data access request (e.g., slice accessrequests A-1-x) to the other DST execution unit 5 when the alternativedata access response indicates forwarding data access requests for theat least a portion of the one of the multitude of encoded data files tothe other DST execution unit. For instance, DST execution unit 1 issuesforwarded slice access requests A-1-x to DST execution unit 5 forfurther processing.

When the processing module 84 of the other DST execution unit 5 receivesthe forwarded slice access requests A-1-x, identifies the other DSTexecution unit 5 of the DST execution unit pool 490 when the alternativedata access response indicates that the other DST execution unit 5 is torespond to data access requests for the at least a portion of the one ofthe multitude of encoded data files when the one of the correspondingportions of the data access request (e.g., A-1-x) is directed towardsthe one of the preferred DST execution units 1-2 having the undesiredperformance level. Having identified the other DST execution unit 5, theprocessing module 84 of the DST execution unit 5 obtains the copy of theat least some of the encoded data slices (e.g., partition slices A-1-x)of the at least a portion of the one of the multitude of encoded datafiles from the memory 88 of the other DST execution unit 5.Alternatively, the processing module 84 of DST execution unit 4retrieves the copy of the at least some of the encoded data slices fromthe memory 88 of the other DST execution unit 5. Having obtained thecopy of the at least some of the encoded data slices, the processingmodule 84 of the DST execution unit 5 sends, via the network interface169 of the DST execution unit 5, the copy the at least some of theencoded data slices of the at least a portion of the one of themultitude of encoded data files to the computing device 492 (e.g., therequesting entity). Alternatively, the processing module 84 of DSTexecution unit 4 sends, via the network interface 169 of the DSTexecution unit 4, the copy the at least some of the encoded data slicesof the at least a portion of the one of the multitude of encoded datafiles to the computing device 492.

The processing module 84 of the one of the preferred DST execution units1-2 having the undesired performance level or another of the preferredDST execution units 3-4 processes the one of or another one of thecorresponding portions of the data access request by sending, via thenetwork interface 169 of the one of the preferred DST execution units1-2 or via the network interface of the other of the preferred DSTexecution units 3-4, at least some of the encoded data slices or anotherat least some of the encoded data slices of the at least a portion ofthe one of the multitude of encoded data files to a requesting entity inaccordance with the modified data access response plan. As a specificexample, the processing module 84 of DST execution unit 1 issues sliceaccess requests B-1-x to the computing device 492 when the other of thecorresponding portions of the data access request pertains to accessingdata file B. As another specific example, the processing module 84 ofDST execution unit 3 issues slice access requests B-3-x to the computingdevice 492 when the other of the corresponding portions of the dataaccess request pertains to accessing data file B. As yet anotherspecific example, the processing module 84 of DST execution unit 3issues slice access requests A-3-x to the computing device 492 when theother of the corresponding portions of the data access request pertainsto accessing data file A.

FIG. 44F illustrates final steps of the example of modifying the DSNmemory data access response plan. When the computing device 492 receivesthe modified data access response plan 510, the computing device 492issues the slice access request 500 directly to the DST execution unitsthat correspond to the modified data access response plan 510. As aspecific example, the computing device 492 issues the slice accessrequest 500 utilizing the slice location table 494 when the slicelocation table 494 has been updated based on the modified data accessresponse plan 510. Having updated the slice location table 494, the DSTclient module 34 issues slice access requests 500 that includes sliceaccess requests A-3-x issued to DST execution unit 3, slice accessrequests A-4-x issued to DST execution unit 4, and slice access requestsA-1-x issued to DST execution unit 5.

Having received the slice access requests A-1-x, the processing module84 of the other DST execution unit 5 processes the one of thecorresponding portions of the data access request (e.g., for a partitionslices A-1-x) by sending, via the network interface 169 of the DSTexecution unit 5, the copy of at least some of the encoded data slicesof the at least a portion of the one of the multitude of encoded datafiles to the computing device 492 when the alternative data accessresponse indicates that the other DST execution unit 5 is to respond todata access requests for the at least a portion of the one of themultitude of encoded data files.

Having received the slice access requests A-3-x, the processing module84 of the DST execution unit 3 sends, via the network interface 169 ofthe DST execution unit 3, slice access responses A-3-x to the computingdevice 492. Having received the slice access requests A-4-x, theprocessing module 84 of the DST execution unit 4 sends, via the networkinterface 169 of the DST execution unit 4, slice access responses A-4-xto the computing device 492. Having received slice access responsesA-3-x, A-4-x, and A-1-x, the DST client module 34 dispersed storageerror decodes received encoded data slices of the slice access responsesto reproduce data file A.

FIG. 44G is a flowchart illustrating an example of modifying a dispersedstorage network (DSN) memory data access response plan. The methodbegins at step 520 where a processing module (e.g., of one or moreprocessing modules executing operational instructions of one or morestorage sections from a computer readable storage medium) obtains dataaccess response performance data for each storage node in a pool ofstorage nodes, where the pool of storage nodes stores a multitude ofencoded data files.

The method continues at step 522 where the processing module analyzesthe data access response performance data for the pool of storage nodesto modify a data access response plan to produce a modified data accessresponse plan. The data access response plan includes, for at least aportion of one of the multitude of encoded data files a per data segmentencoded data slice response level, identity of a set of storage nodesstoring encoded data slices of the at least a portion of the one of themultitude of encoded data files, and identity of preferred storage nodesof the set of storage nodes to respond to a data access request for theat least a portion of the one of the multitude of encoded data files.The data access response plan is modified to include an indication thatone of the preferred storage nodes has an undesired performance leveland to include an alternative data access response for the one of thepreferred storage nodes having the undesired performance level.

The method continues at step 524 where the processing module distributesthe modified data access response plan to one or more of the pool ofstorage nodes and one or more requesting entities. Alternatively, or inaddition to, the method branches to step 538 where the processing moduleforwards the encoded data slices to another storage node and returns tostep 526. For instance, the method branches to step 538 when themodified data access response plan indicates that at least some encodeddata slices associated with the one of the preferred storage nodes thathas the undesired performance level are to be forwarded to anotherstorage node.

The method continues at step 526 where the processing module receivescorresponding portions of the data access request for the at least aportion of the one of the multitude of encoded data files. In response,the processing module may distribute the modified data access responseplan to the one or more requesting entities. As a specific example, theprocessing module distributes the modified data access response plan toa requesting entity of the data access request when at least one of thecorresponding portions of the data access request is directed at astorage node of the storage nodes that is not associated with thecorresponding portion (e.g., the requesting entity sent the at least oneof the corresponding portions of the data access request withoututilizing the modified data access response plan). The method continuesat step 528 where the processing module accesses the modified dataaccess response plan.

The method continues at step 530 where the processing module processesone of the corresponding portions of the data access request inaccordance with the alternative data access response when the one of thecorresponding portions of the data access request is directed towardsthe one of the preferred storage nodes having the undesired performancelevel. As a specific example, the processing module analyzes the dataaccess request to select a processing type. The selecting may be basedon one or more of a predetermination, a DSN performance level, the dataaccess response performance data, and the alternative data accessresponse. The processing type includes at least one of discarding,responding, forwarding the request, and forwarding slices. The methodbranches to step 538 when the processing type includes the forwardingthe slices. The method branches to step 536 when the processing typeincludes the forwarding the request. The method branches to step 534when the processing type includes the responding. The method continuesto step 532 when the processing type includes the discarding.

When the processing type includes the discarding, the method continuesat step 532 where the processing module further processes the one of thecorresponding portions of the data access request by discarding the oneof the corresponding portions of the data access request when thealternative data access response includes an indication that data accessrequests for the at least a portion of the one of the multitude ofencoded data files are to be discarded when the one of the correspondingportions of the data access request is directed towards the one of thepreferred storage nodes having the undesired performance level.

When the processing type includes the responding, the method continuesat step 534 where the processing module further processes the one of thecorresponding portions of the data access request by identifying theother storage node of the pool of storage nodes when the alternativedata access response indicates that the other storage node is to respondto data access requests for the at least a portion of the one of themultitude of encoded data files when the one of the correspondingportions of the data access request is directed towards the one of thepreferred storage nodes having the undesired performance level. Havingidentified the other storage node, the processing module obtains a copyof at least some of the encoded data slices of the at least a portion ofthe one of the multitude of encoded data files from the other storagenode. Having obtained the copy of the at least some of the encoded dataslices, the processing module sends the copy of the at least some of theencoded data slices of the at least a portion of the one of themultitude of encoded data files to a requesting entity.

Alternatively, or in addition to, the processing module furtherprocesses the one of the corresponding portions of the data accessrequest by processing the one of the corresponding portions of the dataaccess request by sending the at least some of the encoded data slicesof the at least a portion of the one of the multitude of encoded datafiles to the requesting entity in accordance with the modified dataaccess response plan. Further alternatively, the processing module mayprocess another of the corresponding portions of the data access requestby sending other of the encoded data slices of the at least a portion ofthe one of the multitude of encoded data files to the requesting entityin accordance with the modified data access response plan.

When the processing type includes the forwarding the request, the methodcontinues at step 536 where the processing module further processes theone of the corresponding portions of the data access request byforwarding the one of the corresponding portions of the data accessrequest to the other storage node of the pool of storage nodes when thealternative data access response indicates forwarding data accessrequests for the at least a portion of the one of the multitude ofencoded data files to the other storage node when the one of thecorresponding portions of the data access request is directed towardsthe one of the preferred storage nodes having the undesired performancelevel.

When the processing type includes the forwarding the slices, the methodcontinues at step 538 where the processing module further processes theone of the corresponding portions of the data access request by, whenthe one of the preferred storage nodes has the undesired performancelevel, identifying the encoded data slices of the at least a portion ofthe one of the multitude of encoded data files. Having identified theencoded data slices, the processing module selects another storage nodeof the pool of storage nodes based on an availability to perform thealternative data access response. Having selected the other storagenode, the processing module facilitates the other storage node storingthe copy of at least some of the encoded data slices of the at least aportion of the one of the multitude of encoded data files.

Alternatively, or in addition to, when the processing type includes theforwarding the slices, the method continues at step 538 where theprocessing module further processes the one of the correspondingportions of the data access request by, when the one of the preferredstorage nodes has the undesired performance level, identifying theencoded data slices of the at least a portion of the one of themultitude of encoded data files. Having identified the encoded dataslices, the processing module selects a set of other storage nodes fromthe pool of storage nodes based on an availability to perform thealternative data access response. Having selected the set of otherstorage nodes, the processing module facilitates the set of otherstorage nodes storing the copy of at least some of the encoded dataslices of the at least a portion of the one of the multitude of encodeddata files. The method branches to step 526 when the forwarding of theencoded data slices to the other storage node follows step 524.

FIG. 45A is a schematic block diagram of another embodiment of adispersed storage system that includes a computing device 550 anddispersed storage (DS) unit pool 552. The DS unit pool 552 includes aplurality of DS units 376 of FIG. 41A. The computing device 550 may beimplemented as one or more of a distributed storage and task (DST) unit,the DST processing unit 16 of FIG. 1, the DST execution unit 36 of FIG.1, the DS unit 376, a storage server, a user device, and a distributedcomputing server.

The system functions to store data in the DS unit pool 552. Thecomputing device 550 selects a set of DS units 376 of the DS unit pool552. The selecting may be based on one or more of DS unit availability,DS unit storage level availability, and DS unit performance. Thecomputing device 550 segments the data based on a segmentation scheme toproduce a plurality of data segments. For each data segment of theplurality of data segments, the computing device 550 issues a set ofwrite slice requests 554 to the set of DS units. The issuing includesgenerating the set of write slice requests 554 (e.g., write slicerequests include a slice and a slice name) and outputting the set ofwrite slice requests 554 to the set of DS units. Each DS unit 376 of theset of DS units receives a corresponding write slice request 554 andprocesses the request to issue a write slice response 556 to thecomputing device 550. The write slice response 556 includes a writestatus indicator (e.g., succeed/failed).

When an unfavorable number of write errors occur, the computing device550 issues at least one incremental write slice request 554 to aremaining DS unit 376 of the DS unit pool 552. The computing device 550detects the unfavorable number of write errors when less than a writethreshold number of write slice responses 556 include a favorableresponse (e.g., succeeded status). The issuing includes selecting theremaining DS unit 376, generating the at least one incremental writeslice request 554, and outputting the at least one incremental writeslice request 554 to the selected remaining DS unit 376. Alternatively,when a favorable number of write errors occur (e.g., at least the writethreshold number of read slice responses are associated with favorableresponses such as the succeeded status), the computing device 550generates a DSN address based on identities of actual DS units utilized.For example, the computing device 550 generates the DSN address by aconcatenating internet protocol addresses of each of the actual DSunits. The DSN addresses may be different for each segment. Thecomputing device 550 updates at least one of a DSN index and a DSNdirectory to associate the DSN address (s) with a data identifier of thedata. As such, a corresponding set of encoded data slices of each datasegment of the plurality of data segments may be stored in differentsets of DS units of the plurality of DS units.

FIG. 45B is a flowchart illustrating an example of storing data. Themethod begins at step 558 where a processing module (e.g., of acomputing device) selects a pillar width number of dispersed storage(DS) units of a DS unit pool for storing data. The selecting may bebased on one or more of storage availability, storage performancehistory, proximity, and affiliation with a requesting entity. The methodcontinues at step 560 where the processing module segments the databased on a segmentation scheme to produce a plurality of segments. Thesegmenting includes obtaining the segmentation scheme from a systemregistry based on a requesting entity identifier.

For each segment of the plurality of segments, the method continues atstep 562 where the processing module issues a pillar width number ofwrite slice requests to the pillar width number of DS units. The issuingincludes encoding the segment using a dispersed storage error codingfunction to produce a pillar width number of slices and generating thewrite slice requests to include a pillar width number of temporary slicenames and the pillar width number of slices. A temporary slice name ofthe pillar width number of temporary slice names may include a uniquedata identifier of data being stored, a segment identifier, and a pillaridentifier.

The method continues at step 564 where the processing module determineswhether an unfavorable number of write errors have occurred. Theprocessing module determines that the unfavorable number of write errorshas occurred when the processing module has not received at least awrite threshold number of favorable (e.g., succeeded status) write sliceresponses. The method branches to step 568 when the unfavorable numberof write errors has not occurred. The method continues to step 566 whenthe unfavorable number of write errors has occurred. The methodcontinues at step 566 where, for each error, the processing modulere-issues a corresponding write slice request to another DS unit ofremaining DS units of the DS unit pool. The re-issuing includesgenerating a new slice name for the slice, generating a new slicerequest to include the new slice name and the slice, and outputting thecorresponding write slice request to the other DS unit. The method loopsback to step 564 where the processing module determines whether theunfavorable number of write errors has occurred.

The method continues at step 568 where the processing module generates aDSN address for the data based on identities of actual DS unitsfavorable utilized when the unfavorable number of write errors has notoccurred. The generating includes producing a portion of the DSN addressbased on a deterministic function applied to each identifier of theactual DS units favorable utilized (e.g., concatenating internetprotocol addresses of the actual DS units favorably utilized). Themethod continues at step 570 where the processing module updates atleast one of a DSN index and a DSN directory to associate the DSNaddress (s) with a data identifier of the data. The updating includesstoring the DSN address in an index entry associated with the dataidentifier. Alternatively, or in addition to, the processing module mayupdate the DS units favorably utilized with the DSN addresses toassociate the DSN addresses with the temporary slice names.

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “operably coupled to”, “coupled to”, and/or “coupling” includesdirect coupling between items and/or indirect coupling between items viaan intervening item (e.g., an item includes, but is not limited to, acomponent, an element, a circuit, and/or a module) where, for indirectcoupling, the intervening item does not modify the information of asignal but may adjust its current level, voltage level, and/or powerlevel. As may further be used herein, inferred coupling (i.e., where oneelement is coupled to another element by inference) includes direct andindirect coupling between two items in the same manner as “coupled to”.As may even further be used herein, the term “operable to” or “operablycoupled to” indicates that an item includes one or more of powerconnections, input(s), output(s), etc., to perform, when activated, oneor more its corresponding functions and may further include inferredcoupling to one or more other items. As may still further be usedherein, the term “associated with”, includes direct and/or indirectcoupling of separate items and/or one item being embedded within anotheritem. As may be used herein, the term “compares favorably”, indicatesthat a comparison between two or more items, signals, etc., provides adesired relationship. For example, when the desired relationship is thatsignal 1 has a greater magnitude than signal 2, a favorable comparisonmay be achieved when the magnitude of signal 1 is greater than that ofsignal 2 or when the magnitude of signal 2 is less than that of signal1.

As may also be used herein, the terms “processing module”, “processingcircuit”, and/or “processing unit” may be a single processing device ora plurality of processing devices. Such a processing device may be amicroprocessor, micro-controller, digital signal processor,microcomputer, central processing unit, field programmable gate array,programmable logic device, state machine, logic circuitry, analogcircuitry, digital circuitry, and/or any device that manipulates signals(analog and/or digital) based on hard coding of the circuitry and/oroperational instructions. The processing module, module, processingcircuit, and/or processing unit may be, or further include, memoryand/or an integrated memory element, which may be a single memorydevice, a plurality of memory devices, and/or embedded circuitry ofanother processing module, module, processing circuit, and/or processingunit. Such a memory device may be a read-only memory, random accessmemory, volatile memory, non-volatile memory, static memory, dynamicmemory, flash memory, cache memory, and/or any device that storesdigital information. Note that if the processing module, module,processing circuit, and/or processing unit includes more than oneprocessing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,and/or processing unit implements one or more of its functions via astate machine, analog circuitry, digital circuitry, and/or logiccircuitry, the memory and/or memory element storing the correspondingoperational instructions may be embedded within, or external to, thecircuitry comprising the state machine, analog circuitry, digitalcircuitry, and/or logic circuitry. Still further note that, the memoryelement may store, and the processing module, module, processingcircuit, and/or processing unit executes, hard coded and/or operationalinstructions corresponding to at least some of the steps and/orfunctions illustrated in one or more of the Figures. Such a memorydevice or memory element can be included in an article of manufacture.

The present invention has been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claimed invention. Further, theboundaries of these functional building blocks have been arbitrarilydefined for convenience of description. Alternate boundaries could bedefined as long as the certain significant functions are appropriatelyperformed. Similarly, flow diagram blocks may also have been arbitrarilydefined herein to illustrate certain significant functionality. To theextent used, the flow diagram block boundaries and sequence could havebeen defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claimed invention. One of average skill in the artwill also recognize that the functional building blocks, and otherillustrative blocks, modules and components herein, can be implementedas illustrated or by discrete components, application specificintegrated circuits, processors executing appropriate software and thelike or any combination thereof.

The present invention may have also been described, at least in part, interms of one or more embodiments. An embodiment of the present inventionis used herein to illustrate the present invention, an aspect thereof, afeature thereof, a concept thereof, and/or an example thereof. Aphysical embodiment of an apparatus, an article of manufacture, amachine, and/or of a process that embodies the present invention mayinclude one or more of the aspects, features, concepts, examples, etc.,described with reference to one or more of the embodiments discussedherein. Further, from figure to figure, the embodiments may incorporatethe same or similarly named functions, steps, modules, etc., that mayuse the same or different reference numbers and, as such, the functions,steps, modules, etc., may be the same or similar functions, steps,modules, etc., or different ones.

While the transistors in the above described figure(s) is/are shown asfield effect transistors (FETs), as one of ordinary skill in the artwill appreciate, the transistors may be implemented using any type oftransistor structure including, but not limited to, bipolar, metal oxidesemiconductor field effect transistors (MOSFET), N-well transistors,P-well transistors, enhancement mode, depletion mode, and zero voltagethreshold (VT) transistors.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of the various embodimentsof the present invention. A module includes a processing module, afunctional block, hardware, and/or software stored on memory forperforming one or more functions as may be described herein. Note that,if the module is implemented via hardware, the hardware may operateindependently and/or in conjunction software and/or firmware. As usedherein, a module may contain one or more sub-modules, each of which maybe one or more modules.

While particular combinations of various functions and features of thepresent invention have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent invention is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. Dispersed storage network (DSN) memory comprises:a pool of storage nodes, wherein each storage node of the pool ofstorage nodes includes a processing module, a network interface, andmemory, and wherein the pool of storage nodes stores a multitude ofencoded data files; the processing module of one or more storage nodesof the pool of storage nodes is operable to: obtain data access responseperformance data for each of the storage nodes in the pool of storagenodes; analyze the data access response performance data for the pool ofstorage nodes to modify a data access response plan to produce amodified data access response plan, wherein the data access responseplan includes, for at least a portion of one of the multitude of encodeddata files: a per data segment encoded data slice response level,identity of a set of storage nodes storing encoded data slices of the atleast a portion of the one of the multitude of encoded data files, andidentity of preferred storage nodes of the set of storage nodes torespond to a data access request for the at least a portion of the oneof the multitude of encoded data files, wherein the data access responseplan is modified to include an indication that one of the preferredstorage nodes has an undesired performance level and to include analternative data access response for the one of the preferred storagenodes having the undesired performance level; and distribute themodified data access response plan to the pool of storage nodes; and theprocessing modules of the preferred storage nodes operable to receive,via the network interfaces of the preferred storage nodes, correspondingportions of the data access request for the at least a portion of theone of the multitude of encoded data files; and the processing module ofthe one of the preferred storage nodes having the undesired performancelevel or the processing module of another storage node of the pool ofstorage nodes operable to process one of the corresponding portions ofthe data access request in accordance with the alternative data accessresponse.
 2. The DSN memory of claim 1, wherein the processing module ofthe one of the preferred storage nodes having the undesired performancelevel functions to process the one of the corresponding portions of thedata access request by: discarding the one of the corresponding portionsof the data access request when the alternative data access responseincludes an indication that data access requests for the at least aportion of the one of the multitude of encoded data files are to bediscarded.
 3. The DSN of claim 1, wherein the processing module of theother storage node functions to process the one of the correspondingportions of the data access request by: sending, via the networkinterface of the other storage node, a copy of at least some of theencoded data slices of the at least a portion of the one of themultitude of encoded data files to a requesting entity when thealternative data access response indicates that the other storage nodeis to respond to data access requests for the at least a portion of theone of the multitude of encoded data files.
 4. The DSN memory of claim1, wherein the processing module of the one of the preferred storagenodes having the undesired performance level functions to process theone of the corresponding portions of the data access request by:forwarding, via the network interface of the one of the preferredstorage nodes, the one of the corresponding portions of the data accessrequest to the other storage node when the alternative data accessresponse indicates forwarding data access requests for the at least aportion of the one of the multitude of encoded data files to the otherstorage node.
 5. The DSN memory of claim 1, wherein the processingmodule of the one or more storage nodes of the pool of storage nodes isfurther operable to: when the one of the preferred storage nodes has theundesired performance level: identify the encoded data slices of the atleast a portion of the one of the multitude of encoded data files;select the other storage node based on an availability to perform thealternative data access response; and facilitate the other storage nodestoring a copy of at least some of the encoded data slices of the atleast a portion of the one of the multitude of encoded data files. 6.The DSN memory of claim 1, wherein the processing module of the one ormore storage nodes of the pool of storage nodes is further operable to:when the one of the preferred storage nodes has the undesiredperformance level: identify the encoded data slices of the at least aportion of the one of the multitude of encoded data files; select a setof other storage nodes from the pool of storage nodes based on anavailability to perform the alternative data access response, whereinthe set of other storage nodes includes the other storage node;facilitate the set of other storage nodes storing a copy of at leastsome of the encoded data slices of the at least a portion of the one ofthe multitude of encoded data files; and select one of the set of otherstorage nodes to function as the other storage node.
 7. The DSN memoryof claim 1, wherein the one of the multitude of encoded data filesfurther comprises: a plurality of data partitions, wherein a datapartition of the plurality of data partitions includes one portion ofthe at least a portion of the one of the multitude of encoded datafiles, wherein the data partition includes a plurality of data segments,and wherein a data segment of the plurality of data segments isdispersed storage error encoded to produce a set of encoded data slices.8. The DSN memory of claim 1, wherein the processing module of the oneor more storage nodes of the pool of storage nodes is further operableto: distribute the modified data access response plan to one or morerequesting entities by at least one of: sending, via the networkinterface of the one or more storage nodes, the modified data accessresponse plan to the one or more requesting entities; updating a systemregistry to include the modified data access response plan; and issuinga slice access response to one of the one or more requesting entities,wherein the slice access response includes the modified data accessresponse plan, when receiving a slice access request from the one of theone or more requesting entities.
 9. The DSN memory of claim 1, whereinthe multitude of encoded data files comprises: a first data file encodedin accordance with a first set of dispersed storage error encodingparameters; and a second data file encoded in accordance with a secondset of dispersed storage error encoding parameters.
 10. The DSN memoryof claim 1 further comprises: the processing module of the one of thepreferred storage nodes having the undesired performance level oranother of the preferred storage nodes is operable to process another ofthe corresponding portions of the data access request by sending, viathe network interface of the one of the preferred storage nodes or viathe network interface of the other of the preferred storage nodes, atleast some of the encoded data slices of the at least a portion of theone of the multitude of encoded data files to a requesting entity inaccordance with the modified data access response plan.
 11. A computerreadable storage medium comprises: a first storage section that storesoperational instructions that, when executed by one or more processingmodules, causes the one or more processing modules to: obtain dataaccess response performance data for each storage node in a pool ofstorage nodes, wherein the pool of storage nodes stores a multitude ofencoded data files; analyze the data access response performance datafor the pool of storage nodes to modify a data access response plan toproduce a modified data access response plan, wherein the data accessresponse plan includes, for at least a portion of one of the multitudeof encoded data files: a per data segment encoded data slice responselevel, identity of a set of storage nodes storing encoded data slices ofthe at least a portion of the one of the multitude of encoded datafiles, and identity of preferred storage nodes of the set of storagenodes to respond to a data access request for the at least a portion ofthe one of the multitude of encoded data files, wherein the data accessresponse plan is modified to include an indication that one of thepreferred storage nodes has an undesired performance level and toinclude an alternative data access response for the one of the preferredstorage nodes having the undesired performance level; and distribute themodified data access response plan to the pool of storage nodes; and asecond storage section that stores operational instructions that, whenexecuted by the one or more processing modules, causes the one or moreprocessing modules to: receive, via one or more network interfaces,corresponding portions of the data access request for the at least aportion of the one of the multitude of encoded data files; access themodified data access response plan; and process one of the correspondingportions of the data access request in accordance with the alternativedata access response when the one of the corresponding portions of thedata access request is directed towards the one of the preferred storagenodes having the undesired performance level.
 12. The computer readablestorage medium of claim 11, wherein the one or more processing modulesfunctions to process the one of the corresponding portions of the dataaccess request by: discarding the one of the corresponding portions ofthe data access request when the alternative data access responseincludes an indication that data access requests for the at least aportion of the one of the multitude of encoded data files are to bediscarded when the one of the corresponding portions of the data accessrequest is directed towards the one of the preferred storage nodeshaving the undesired performance level.
 13. The computer readablestorage medium of claim 11, wherein the one or more processing modulesfunctions to process the one of the corresponding portions of the dataaccess request by: identifying another storage node of the pool ofstorage nodes when the alternative data access response indicates thatthe other storage node is to respond to data access requests for the atleast a portion of the one of the multitude of encoded data files whenthe one of the corresponding portions of the data access request isdirected towards the one of the preferred storage nodes having theundesired performance level; obtaining a copy of at least some of theencoded data slices of the at least a portion of the one of themultitude of encoded data files from the other storage node; andsending, via a network interface of the one or more network interfaces,the copy the at least some of the encoded data slices of the at least aportion of the one of the multitude of encoded data files to arequesting entity.
 14. The computer readable storage medium of claim 11,wherein the one or more processing modules functions to process the oneof the corresponding portions of the data access request by: forwardingthe one of the corresponding portions of the data access request toanother storage node of the pool of storage nodes when the alternativedata access response indicates forwarding data access requests for theat least a portion of the one of the multitude of encoded data files tothe other storage node when the one of the corresponding portions of thedata access request is directed towards the one of the preferred storagenodes having the undesired performance level.
 15. The computer readablestorage medium of claim 11 further comprises: the first storage sectionstores further operational instructions that, when executed by the oneor more processing modules, causes the one or more processing modulesto: when the one of the preferred storage nodes has the undesiredperformance level: identify the encoded data slices of the at least aportion of the one of the multitude of encoded data files; selectinganother storage node of the pool of storage nodes based on anavailability to perform the alternative data access response; andfacilitate the other storage node storing a copy of at least some of theencoded data slices of the at least a portion of the one of themultitude of encoded data files.
 16. The computer readable storagemedium of claim 11 further comprises: the first storage section storesfurther operational instructions that, when executed by the one or moreprocessing modules, causes the one or more processing modules to: whenthe one of the preferred storage nodes has the undesired performancelevel: identify the encoded data slices of the at least a portion of theone of the multitude of encoded data files; select a set of otherstorage nodes from the pool of storage nodes based on an availability toperform the alternative data access response; and facilitate the set ofother storage nodes storing a copy of at least some of the encoded dataslices of the at least a portion of the one of the multitude of encodeddata files.
 17. The computer readable storage medium of claim 11,wherein the one of the multitude of encoded data files furthercomprises: a plurality of data partitions, wherein a data partition ofthe plurality of data partitions includes one portion of the at least aportion of the one of the multitude of encoded data files, wherein thedata partition includes a plurality of data segments, and wherein a datasegment of the plurality of data segments is dispersed storage errorencoded to produce a set of encoded data slices.
 18. The computerreadable storage medium of claim 11 further comprises: the first storagesection stores further operational instructions that, when executed bythe one or more processing modules, causes the one or more processingmodules to: distribute the modified data access response plan to one ormore requesting entities by at least one of: sending, via the one ormore network interfaces, the modified data access response plan to theone or more requesting entities; updating a system registry to includethe modified data access response plan; and issuing a slice accessresponse to one of the one or more requesting entities, wherein theslice access response includes the modified data access response plan,when receiving a slice access request from the one of the one or morerequesting entities.
 19. The computer readable storage medium of claim11, wherein the multitude of encoded data files comprises: a first datafile encoded in accordance with a first set of dispersed storage errorencoding parameters; and a second data file encoded in accordance with asecond set of dispersed storage error encoding parameters.
 20. Thecomputer readable storage medium of claim 11 further comprises: thesecond storage section stores further operational instructions that,when executed by the one or more processing modules, causes the one ormore processing modules to: process the one of the correspondingportions of the data access request by sending, via the one or morenetwork interfaces, at least some of the encoded data slices of the atleast a portion of the one of the multitude of encoded data files to arequesting entity in accordance with the modified data access responseplan; and process another one of the corresponding portions of the dataaccess request by sending, via the one or more network interfaces,another at least some of the encoded data slices of the at least aportion of the one of the multitude of encoded data files to therequesting entity in accordance with the modified data access responseplan.